From talks@list.cs.brown.edu Mon Jan 12 19:46:32 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Mon, 12 Jan 2004 14:46:32 -0500 Subject: [Brown CS Talks] Silvio Savarese will be giving a talk on 2/2/04 at noon in Division of Engineering, Room 190 Message-ID: <006401c3d944$c7d16be0$0c269480@cs.brown.edu> Joint SHAPE Lab and LEMS seminar BROWN UNIVERSITY Silvio Savarese California Institute of Technology Monday, February 2, 2004 at noon Division of Engineering, Room 190 Perception and 3D Reconstruction of Specular Surfaces Perception and 3D Reconstruction of Specular Surfaces One of the main tasks of a visual system is computing the shape of objects. A number of cues, notably stereoscopic disparity, texture gradient, motion parallax, contours and shading, have been shown to carry valuable information on surface shape, and have been studied extensively. Unfortunately, many objects of interest and most man-made surfaces, such as a silver plate, a metal spoon or a clean automobile, are smooth and shiny, violating the hypotheses that underlie the analysis of those cues. For specular objects, however one additional cue may be precisely the reflection of the environment: a deformed picture of the surrounding scene can be seen on the surface of the specular object and amount and type of deformation depend upon its shape. Our research is aimed at understanding how the human visual system uses this cue in shape perception and what is the relationship relating deformations and local geometry of the surface. To this effect, we assume a simple calibrated scene composed of lines passing through a point (e.g. a checherboard pattern). Under these hypotheses, we demonstrated that local information about the geometry of the surface can be fully recovered up to third order from orientation and local scale of the reflected images of (at least) two intersecting lines. Host: Professor Gabriel Taubin From talks@list.cs.brown.edu Mon Jan 12 19:46:35 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Mon, 12 Jan 2004 14:46:35 -0500 Subject: [Brown CS Talks] Li Fei-fei will be giving a talk on 2/3/04 at noon in Division of Engineering, Room 190 Message-ID: <006501c3d944$ca23e760$0c269480@cs.brown.edu> Joint SHAPE Lab and LEMS seminar BROWN UNIVERSITY Li Fei-Fei California Institute of Technology Tuesday, February 3, 2004 at noon Division of Engineering, Room 190 A Bayesian Framework for Unsupervised One-Shot Learning of Object Categories Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires models containing hundreds of parameters. We present a method for learning object categories from just a few images (1~5). It is based on incorporating ``generic'' knowledge which may be obtained from previously learnt models of unrelated categories. We operate in a variational Bayesian framework: object categories are represented by probabilistic models, and ``prior'' knowledge is represented as a probability density function on the parameters of these models. The ``posterior'' model for an object category is obtained by updating the prior in the light of one or more observations. Our ideas are demonstrated on objects belonging to 101 widely varied categories. Two learning schemes within the variational Bayesian framework are tested: batch learning and incremental learning. We show that the variational Bayes methods are capable of learning a very wide range of object categories using very few training images. While the batch and incremental methods have comparable performances, the incremental one has much shorter learning time. Host: Professor Gabriel Taubin From talks@list.cs.brown.edu Tue Jan 20 21:34:06 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 20 Jan 2004 16:34:06 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Irv Lustig in Lubrano on 1/30/04 at noon Message-ID: <20040120213406.3EF442F01F@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Irv Lustig ILOG Friday, January 30, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Scheduling the NFL with Constraint Programming The National Football League (NFL) consists of 32 teams, with each team playing a predetermined set of 16 games and one bye over 17 weeks. The NFL has to schedule these games to meet the demands of the teams as well as the television networks. We describe how constraint programming has been successfully applied to solve this problem, and how the NFL used the solution to compute the 2003 NFL schedule. Dr. Irv Lustig holds an Sc.B. in Applied Mathematics/Computer Science from Brown (1983) and a Ph.D. in Operations Research from Stanford (1987) under G. Dantzig. He was awarded the 1992 INFORMS ICS Prize and the 1991 Beale-W.B. Orchard-Hays Prize from the Mathematical Programming Society for his work on interior-point methods. Dr. Lustig has taught at Princeton University and was a member of the CPLEX development team, where he was responsible for all CPLEX presolve and barrier algorithms. He is now manager of technical services for ILOG Direct. Host: Professor Pascal Van Hentenryck From talks@list.cs.brown.edu Thu Jan 29 16:52:16 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 29 Jan 2004 11:52:16 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Kelly Gaither in Lubrano on 2/3/04 at noon Message-ID: <20040129165217.1049E2EFDA@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Kelly Gaither Texas Advanced Computing Center Tuesday, February 3, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Statistically Based Volumetric Feature Identification Current approaches to volumetric feature detection depend on some a priori knowledge of the data, requiring the analyst to make assumptions about both existence and location of phenomena which may or may not exist in the domain. Phenomenological existence and location is determined using analytical methods, while behavior is characterized by statistical analysis computed on the features once they are abstracted from the volume. While successful, this two-phase approach is subjective in nature and provides no generalized characterizations of the volume. We have been working on a new feature-detection paradigm consisting of three phases. In the first phase, the volume is segmented into potential feature clusters and each cluster is characterized by a series of statistical properties. The second phase incorporates domain-specific definitions, heuristics, and analytical descriptions that further refine the potential features into true features. These true features are then statistically analyzed to provide relevance and correctness measures. Justifications and implications for this shift in paradigm, as they pertain to the visualization and analysis of computational fluid dynamics data sets, will be presented and discussed. Hosts: David Laidlaw and Cullen Jackson From talks@list.cs.brown.edu Thu Jan 29 16:53:24 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 29 Jan 2004 11:53:24 -0500 Subject: [Brown CS Talks] Brown CS and Brain Science Program Seminar: John Allman in Lubrano on 2/9/04 at 4 pm Message-ID: <20040129165324.BE4972EFF8@null.cs.brown.edu> The Department of Computer Science and Brain Science Program BROWN UNIVERSITY John Allman California Institute of Technology Monday, February 9, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) The Spindle Cells of Anterior Cingulate and Fronto-insular Cortex The spindle cells are large bipolar neurons located in layer 5 of anterior cingulate (ACC) and fronto-insular (FI) cortex. They are present only in humans and apes and are much more numerous in humans than in apes. The spindle neurons are labeled with antibodies for several neurotransmitter receptors that provide clues to their functioning. They express the dopamine D3 receptor, which is involved in the anticipation of reward, and the vasopressin 1A receptor, which in other species mediates the formation of mate preference and social bonding. In fMRI studies involving gambling tasks, the activity of both ACC and FI increase as a function of uncertainty, and these areas are specifically activated in situations in which the subject sustains a loss followed by a decision to change strategy. Both ACC and FI are also activated by images of a love partner. Area FI is activated by feelings of intense guilt, by embarrassment following the violation of social norms, and by the sounds of a crying infant in mothers. The spindle neurons may be part of the neural circuitry for social decision making under conditions of intense motivation and high uncertainty. Host: Professor David Laidlaw From talks@list.cs.brown.edu Thu Jan 29 16:54:27 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 29 Jan 2004 11:54:27 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Kevin Murphy in Lubrano on 2/6/04 at 3 pm Message-ID: <20040129165428.2A6592EFDA@null.cs.brown.edu> The Computer Science Vision and Learning Seminar Series BROWN UNIVERSITY Kevin Murphy MIT Friday, February 6, 2004 at 3 pm Lubrano Conference Room (CIT 4th floor) Using the forest to see the trees: a graphical model relating features, objectsand scenes Detecting objects, such as faces or cars, in images is an important but difficult problem. Most current approaches try to classify each local image patch in isolation, disregarding the rest of the image. Such local approaches may suffer from inherent ambiguities. In addition, it is computationally expensive to find the right local regions to classify, often requiring exhaustive search in position and scale. We show how using a low-dimensional summary of the whole image (the ``gist'' of the image) can ameliorate both problems, since the gist can provide a prior on what kinds of objects to expect, and where to expect them. The gist can also be used to recognize ``scenes'', or correlated patterns of object co-occurrences. We model the dependencies between scenes and objects using a discriminatively trained graphical model, which combines global and local information. Joint work with Antonio Torralba and Bill Freeman Host: Professor Michael Black From talks@list.cs.brown.edu Wed Feb 4 15:16:20 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 4 Feb 2004 10:16:20 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Hanspeter Pfister in Lubrano today at 4 pm Message-ID: <20040204151619.91ED82F024@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Hanspeter Pfister MERL Wednesday, February 4, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Data-Driven Computer Graphics The field of computer graphics offers many modeling and simulation problems. Among these are the representation of surface shape, the description of surface reflectance, the probabilistic modeling of small-scale variations, and the application of physics for simulating the dynamics of rigid and elastic materials. During its formative years, computer graphics has focused largely on developing algorithms and systems for performing efficient simulations that transform these analytic representations into images and animations. At present, this simulation framework for computer graphics is very mature. In last ten years, we have also witnessed significant technological developments in the areas of high-quality sensors and measurement devices. However, the data provided from these devices are frequently incompatible with the representations assumed by most computer graphics systems. In this talk I will explore new approaches to computer graphics that attempt to bridge the dichotomy between parametric and empirical modeling. These approaches differ from the classical analytic models that pervade today's computer graphics, and instead depend more on cameras for data acquisition, machine learning for interpolation and extrapolation, and signal processing for synthesis. I will discuss three specific computer graphics applications of data-driven modeling in this talk. The first, called image-based 3D photography, addresses the problem of creating and rendering high-quality computer graphics models of arbitrary real-world objects. Second, I will discuss the problem of interpolating and extrapolating new reflectance models (specifically isotropic BRDFs) from a collection of acquired samples. Finally, I will present a practical system for performance-driven animations or video rewrite of faces using a multilinear data-driven model and identity and performance parameters that are lifted directly from video. Hosts: David Laidlaw and Andy van Dam From talks@list.cs.brown.edu Tue Feb 10 16:42:38 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 10 Feb 2004 11:42:38 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Erik B. Sudderth and Alexander T. Ihler in Lubrano 2/20/04 at 3 pm Message-ID: <20040210164239.165072EFB1@null.cs.brown.edu> Vision and Learning Seminar Series BROWN UNIVERSITY Computer Science Department Erik B. Sudderth and Alexander T. Ihler MIT Friday, February 20, 2004 at 3 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 2:45 pm Nonparametric Belief Propagation Graphical models provide a powerful general framework for formulating and solving problems of statistical inference and machine learning. In many applications of graphical models, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. However, due to the limitations of existing inference algorithms, it is often necessary to form coarse, discrete approximations to such models. In this talk, we describe a nonparametric belief propagation (NBP) algorithm, that uses stochastic methods to propagate kernel-based approximations to the true continuous messages. Each NBP message update requires approximating the product of several Gaussian mixtures; we present efficient procedures for sampling from this product using multiscale representations. We demonstrate NBP's effectiveness on two different applications: visual recognition and tracking of complex objects, and distributed self-localization of an ad hoc sensor network. Host: Professor Michael Black From talks@list.cs.brown.edu Thu Feb 12 20:49:35 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 12 Feb 2004 15:49:35 -0500 Subject: [Brown CS Talks] Brown CS Theory Colloquium: Eli Ben-Sasson in Lubrano on 2/18/04 at 4 pm Message-ID: <20040212204942.1B17B2F026@null.cs.brown.edu> BROWN UNIVERSITY THEORY COLLOQUIUM Eli Ben-Sasson Radcliffe Institute for Advanced Study at Harvard University Wednesday, February 18, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Robust PCPs of Proximity, Short PCPs, and Applications to Coding The PCP theorem [AS, ALMSS] specifies a way of encoding any mathematical proof such that the validity of the proof can be verified probabilistically by querying the proof only at a constant number of locations. Furthermore, this encoding is complete and sound, i.e., valid proofs are always accepted while invalid proofs are accepted with probability at most 1/2. A natural question that arises in the construction of PCPs is by how much does this encoding blow up the original proof while retaining the constant number of queries into the proof. We study the trade-off between the length of PCPs and their query complexity, and produce the shortest known PCPs (to date), of nearly linear size. In this talk, intended for a general audience, we'll describe some of the tools used to obtain these highly-efficient PCPs, and some of their applications. Our techniques include the introduction of a new variant of PCPs that we call ``Robust PCPs of Proximity''. These new PCPs facilitate proof composition, which is a central ingredient in construction of PCP systems. (A related notion was independently discovered by Dinur and Reingold.) We also obtain analogous quantitative results for locally testable codes. In addition, we introduce a relaxed notion of locally decodable codes, and present such codes mapping k information bits to codewords of length k^{1+e}, for any e>0. Joint work with: Oded Goldreich (Weizmann & Radcliffe), Prahladh Harsha (MIT), Madhu Sudan (MIT & Radcliffe) and Salil Vadhan (Harvard & Radcliffe). Host: Professor Anna Lysyanskaya From talks@list.cs.brown.edu Thu Feb 12 21:20:35 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 12 Feb 2004 16:20:35 -0500 Subject: [Brown CS Talks] Brown CS Theory Colloquium: Boaz Patt Shamir in Lubrano on 2/25/04 at 4 pm Message-ID: <20040212212034.3529E2EF9A@null.cs.brown.edu> BROWN UNIVERSITY THEORY COLLOQUIUM Boaz Patt Shamir Tel Aviv University (currently visiting HP Labs) Wednesday, February 25, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Effective Collaboration Without Trust in Peer-to-Peer Systems We formalize and analyze a simple model for reputation systems, which are expected to be a central part of the infrastructure of peer-to-peer systems. In our model there are n players, some of which may exhibit arbitrarily malicious (Byzantine) behavior, and there are m objects, some of which are bad. The goal of the honest players is to find a good object. To facilitate collaboration, the system maintains a shared billboard. A basic step of a player consists of consulting the billboard, probing an object to learn its true value, and posting the result on the billboard for the benefit of others. Probing an object incurs a cost to the player, and consulting the billboard is free. The dilemma of an honest player is how to balance between the desire to reduce her cost by taking advantage of the reports posted by honest peers, and the fear of being exploited by adopting reports posted by malicious players. As we show, if an alpha fraction of players are honest, then no algorithm can guarantee expected running time smaller than Omega {1 alpha}; our main result is a randomized algorithm that guarantees, for each player, expected running time of O log n (alpha log log n) even when there is just one good object and O(n) bad objects. The result holds for any alpha>0, with improved bounds for alpha close to 1. We also present a few simple generalizations of our algorithm: First, to the model where each object has a different cost, and the goal is to minimize the cost per player; and second, to the model where each object has a real numeric value, and the goal is to find the object of maximal value, where that maximum is unknown in advance. Finally, we study a repeated game variant of our model. Using a different algorithm, we prove that the expected gain for a dishonest player is at most O(log n), which allows the system to cheaply discourage dishonesty. Joint work with B. Awerbuch, D. Peleg and M. Tuttle. Host: Professor Anna Lysyanskaya From talks@list.cs.brown.edu Mon Feb 16 20:51:13 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Mon, 16 Feb 2004 15:51:13 -0500 Subject: [Brown CS Talks] Brown CS Colloquium: Andrei Broder in Lubrano on 2/19/04 at 4 pm Message-ID: <20040216205113.E9EB02F004@null.cs.brown.edu> BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Andrei Broder IBM Research Thursday, February 19, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Sic Transit Gloria Talae: Towards an Understanding of the Web's Decay The rapid growth of the World Wide Web has been noted, tracked, and modeled extensively. However, recent studies have documented the dual phenomenon: web pages have short half lives, and thus the Web exhibits rapid death as well. Consequently, page creators are faced with an increasingly difficult task of keeping links and content up-to-date: many pages are seldom updated, becoming ``decayed'', and less effective as information resources. In this work we formalize a page ``decay'' measure based solely on the Web graph properties and present algorithms for computing it efficiently. We explore this measure by presenting a number of validations, and use it to identify interesting artifacts on today's Web. We then describe a number of potential applications of interest to search engines, web page maintainers, ontologists, and individual users. There are many open questions: Can this measure be made more accurate by combining it with NLP page content analysis? Can we make decay inferences from observed page changes over a long time period? What is a good birth/death model for the Web graph that agrees with our empirical observations? Time permitting, we will explore these and more. This is joint work with Ziv Bar-Yossef, Ravi Kumar, and Andrew Tomkins. Host: Professor Eli Upfal From talks@list.cs.brown.edu Thu Feb 19 16:16:10 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 19 Feb 2004 11:16:10 -0500 Subject: [Brown CS Talks] Brown CS Theory Colloquium: Boaz Patt Shamir in Lubrano on 3/3/04 at 4 pm Message-ID: <20040219161611.3885F2EFF9@null.cs.brown.edu> Please note: The date for this talk is changed to March 3rd, 2004, instead February 25th. BROWN UNIVERSITY THEORY COLLOQUIUM Boaz Patt Shamir Tel Aviv University (currently visiting HP Labs) Wednesday, March 3, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Effective Collaboration Without Trust in Peer-to-Peer Systems We formalize and analyze a simple model for reputation systems, which are expected to be a central part of the infrastructure of peer-to-peer systems. In our model there are n players, some of which may exhibit arbitrarily malicious (Byzantine) behavior, and there are m objects, some of which are bad. The goal of the honest players is to find a good object. To facilitate collaboration, the system maintains a shared billboard. A basic step of a player consists of consulting the billboard, probing an object to learn its true value, and posting the result on the billboard for the benefit of others. Probing an object incurs a cost to the player, and consulting the billboard is free. The dilemma of an honest player is how to balance between the desire to reduce her cost by taking advantage of the reports posted by honest peers, and the fear of being exploited by adopting reports posted by malicious players. As we show, if an alpha fraction of players are honest, then no algorithm can guarantee expected running time smaller than Omega {1 alpha}; our main result is a randomized algorithm that guarantees, for each player, expected running time of O log n (alpha log log n) even when there is just one good object and O(n) bad objects. The result holds for any alpha>0, with improved bounds for alpha close to 1. We also present a few simple generalizations of our algorithm: First, to the model where each object has a different cost, and the goal is to minimize the cost per player; and second, to the model where each object has a real numeric value, and the goal is to find the object of maximal value, where that maximum is unknown in advance. Finally, we study a repeated game variant of our model. Using a different algorithm, we prove that the expected gain for a dishonest player is at most O(log n), which allows the system to cheaply discourage dishonesty. Joint work with B. Awerbuch, D. Peleg and M. Tuttle. Host: Professor Anna Lysyanskaya From talks@list.cs.brown.edu Fri Feb 20 21:56:11 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Fri, 20 Feb 2004 16:56:11 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Christine Julien in Lubrano on 3/9/04 at noon Message-ID: <20040220215612.2C0EC2EFAA@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Christine Julien Washington University Tuesday, March 9, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am A Software Engineering Perspective on Context-Awareness in Ad Hoc Mobile Networks Ad hoc networks form opportunistically and change rapidly in response to the movement of mobile hosts. These networks present new software engineering challenges, especially given the increasing demand for applications tailored to a wide variety of domains. Applications executing in ad hoc networks need to react continuously and rapidly to changes in operating conditions and must adapt their behavior accordingly. Such applications fall in the category of context-aware computing, a field that has received much recent attention. Much of the current work on context-aware computing is limited to presenting only specific types of context information, e.g., location or time. In addition, current context-aware systems often rely only on information directly available to an application via context sensors on the local host. In this talk, I introduce a novel perspective on context-awareness in which the context includes, in principle, any information available in the ad hoc network but is restricted, in practice, to specific projections of the overall context. I will present the design and implementation of a new middleware model that delivers this notion of context to the application programmer. Specifically, the middleware introduces the ability for particular tasks to operate over dynamically and declaratively specified abstract views of the global context. Despite the fact that interactions among hosts in the underlying network are transient and disconnections are frequent, the middleware continuously maintains the desired contextual information. I also present novel network protocols that provide the context-maintenance required to support the middleware's implementation. The resulting context-aware middleware eases the software engineering challenges encountered when programming applications for ad hoc mobile environments. Host: Professor Shriram Krishnamurthi From talks@list.cs.brown.edu Tue Feb 24 16:10:50 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 24 Feb 2004 11:10:50 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Wanghong Yuan in Lubrano on 3/10/04 at noon Message-ID: <20040224161050.AB2B62F071@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Wanghong Yuan University of Illinois Wednesday, March 10, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am GRACE-OS: An Energy-Efficient Mobile Multimedia Operating System Multimedia-enabled mobile devices need to support multimedia quality and save energy. Although the requirement of high quality and low energy is challenging, it is an achievable goal due to the strong advances in adaptable system layers, ranging from hardware to applications. The adaptability, however, introduces two new challenges for the operating system: First, how to coordinate the adaptation of multiple layers in response to changes at different time granularity? Second, how to schedule soft real-time multimedia applications on dynamic hardware? To address these challenges, we have designed, implemented, and evaluated a novel operating system, called GRACE-OS. GRACE-OS takes a hierarchical cross-layer adaptation approach to balance the adaptation benefits and cost. In response to long-term, large changes such as application entry, GRACE-OS coordinates all layers to achieve a system-wide optimization, for example, to maximize multimedia quality for the given battery energy and life. In response to frequent, small variations in application CPU demand, GRACE-OS adapts application execution speed to minimize energy. To adapt speed efficiently, GRACE-OS introduces speed as another dimension of real-time scheduling. That is, it decides how fast to execute applications in addition to what applications to execute and when to execute them. It makes these scheduling decisions based on the probability distribution of CPU demand of individual applications. We have implemented and evaluated GRACE-OS with adaptive Athlon processor and multimedia codecs. Compared to previous systems that adapt one or two layers or adapt only at coarse granularity, GRACE-OS can improve multimedia quality by 22% to 59% while achieving the desired battery life. Host: Professor Ugur Cetintemel From talks@list.cs.brown.edu Tue Feb 24 16:22:13 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 24 Feb 2004 11:22:13 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Amol Deshpande in Lubrano on 3/16/04 at noon Message-ID: <20040224162213.E17E52F07C@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Amol Deshpande University of California Tuesday, March 16, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Adaptive Query Processing to Handle Estimation Errors Adaptive query processing has emerged as an attractive solution to dynamically changing runtime environments, and unknown data distributions in many scenarios. These scenarios involve querying over web sources where little information is usually available about the data sources, continuous query processing where the data characteristics change frequently, and even single site database systems where in many cases, only unreliable statistics are available. Probably the most aggressive of the adaptive query processing techniques proposed is eddies, which continuously reoptimizes a query by changing the order in which operators are applied to tuples on a per-tuple basis. We observe that, even though the eddy can, in principle, choose to route each tuple in a different order, the query execution plans it can affect for multi-join queries can be significantly constrained by the routing decisions it made early during the query execution. In this talk, I will present a modified eddy architecture, called STAIRs, that allows the eddy to manipulate the state stored inside operators, and thereby lift the burden of routing history. I will also discuss our implementation of eddies in the PostgreSQL data management system, and show that the benefits of such adaptivity can be had at a very low cost. Finally, I will briefly discuss some of my recent work on exploiting correlated attributes in sensor network query processing. Host: Professor Stan Zdonik From talks@list.cs.brown.edu Fri Feb 27 19:38:37 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Fri, 27 Feb 2004 14:38:37 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Godmar Back in Lubrano on 3/5/04 at noon Message-ID: <20040227193828.5525B2EFDA@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Godmar Back Stanford University Friday, March 5, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Processes in KaffeOS: Isolation, Resource Management, and Sharing for Java Single-language runtime systems, such as Java virtual machines, are widely deployed platforms for executing untrusted code. These runtimes provide some of the features that operating systems provide: inter-application memory protection and basic system services. They do not, however, provide the ability to isolate applications from each other, or limit their resource consumption. In this talk, I will present KaffeOS, a Java runtime system that provides these features. The KaffeOS architecture takes many lessons from operating system design, such as the use of a user/kernel boundary, and employs garbage collection techniques, such as write barriers. It supports the OS abstraction of a process in a Java virtual machine. Each process executes as if it were run in its own virtual machine, including separate garbage collection of its own heap. The difficulty in designing KaffeOS lay in balancing the goals of isolation and resource management against the goal of allowing direct sharing of objects to enhance performance and scalability. I will present performance results that show that KaffeOS can be used to effectively thwart denial-of-service attacks by untrusted or misbehaving code, and demonstrate the effectiveness of KaffeOS's sharing model. Finally, I will also discuss what I view should be the next steps in making type-safe language runtime systems ready for use in robust and scalable multi-process environments. Godmar Back works as a postdoctoral researcher with Professor Dawson Engler. He received his PhD from the University of Utah in 2002. His research interests lie at the intersection of systems and programming languages. He currently works on MJ, a system for statically checking Java code. Before coming to Stanford, he designed and implemented KaffeOS, a Java runtime system that provides process isolation and resource management for multiple applications in a single JVM. He has also worked on various OS projects, such as the Utah OSKit and the Fluke microkernel. Host: Shriram Kirshnamurthi From talks@list.cs.brown.edu Fri Feb 27 22:46:10 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Fri, 27 Feb 2004 17:46:10 -0500 Subject: [Brown CS Talks] Brown CS 25th Anniversary Distinguished Lecture: John Guttag in Lubrano on 3/4/04 at 4 pm Message-ID: <20040227224552.B8ED22EFE1@null.cs.brown.edu> 25th Anniversary Distinguished Lecture BROWN UNIVERSITY The Computer Science Department John Guttag Head, EECS Dept., MIT Thursday, March 4, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) A reception will follow the talk Sensor-Based Medical Decision Systems A typical medical environment is full of excellent (often expensive) hardware devices for gathering data about the state of a patient. Unfortunately, relatively little attention has been devoted to developing high quality software for integrating, analyzing, and presenting this information. This talk will briefly outline the problem, and then describe a novel hardware/software system designed to attack it. The talk will conclude with two applications: a machine-learning based system for early detection of epileptic seizures, and a system that combines an electronic stethoscope and software to screen for cardiac disease. Both applications have been tested on patients, and highly encouraging preliminary results will be reported. Host: Professor John Savage From talks@list.cs.brown.edu Tue Mar 2 21:52:01 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 2 Mar 2004 16:52:01 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Stefan Saroiu in Lubrano on 3/18/04 at noon Message-ID: <20040302215201.333212F004@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Stefan Saroiu University of Washington Thursday, March 18, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Content Delivery in the Modern Internet In recent years, the Internet has experienced an astronomical increase in the use of specialized content delivery systems, such as peer-to-peer file-sharing systems (e.g., Kazaa, Gnutella, or Napster) and content delivery networks (e.g., Akamai). The sudden popularity of peer-to-peer file-sharing systems has resulted in a flurry of research activity into novel peer-to-peer system designs. Because these systems (1) are fully distributed, without any infrastructure that can be directly measured, (2) have novel distributed designs requiring new crawling techniques, and (3) use proprietary protocols, surprisingly little is known about the performance, behavior, and workload of such systems in practice. This talk remedies this situation. We examine content delivery from the point of view of four content delivery systems: HTTP Web traffic, the Akamai content delivery network, and Kazaa and Gnutella peer-to-peer file sharing networks. Our results (1) quantify the rapidly increasing importance of new content delivery systems, particularly peer-to-peer networks, and (2) characterize peer-to-peer systems both from an infrastructure and workload perspective. Overall, these results provide a new understanding of the behavior of the modern Internet and present a strong basis for the design of newer content delivery systems. At the end of the talk, we present a recent characterization of a new Internet security threat: the spread of spyware. We examine four spyware programs (Gator, Cydoor, SaveNow and eZula) for which we derived signatures that can be used to detect their presence on remote computers through passive network monitoring. Using these signatures, we quantify the spread of spyware within the University of Washington. Our results show that these four programs affect approximately 5.1% of active hosts on campus. Host: Professor Ugur Cetintemel From talks@list.cs.brown.edu Tue Mar 2 22:04:28 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 2 Mar 2004 17:04:28 -0500 Subject: [Brown CS Talks] Brown CS Colloquium: Tim Roughgarden in Lubrano on 3/18/04 at 4 pm Message-ID: <20040302220427.4C7832F047@null.cs.brown.edu> BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Tim Roughgarden UC Berkeley Thursday, March 18, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Selfish Routing and the Price of Anarchy A recent trend in algorithm design is the study of game-theoretic environments, in which individual agents act according to their own independent and conflicting interests. The well-studied objective of routing traffic in a network to achieve the best possible network performance has emerged as a central problem in this area. In large networks, it can be difficult or even impossible to impose optimal routing strategies on network traffic. On the other hand, permitting network users to act according to their own competing interests precludes any type of global optimality, and therefore carries the cost of decreased network performance. This inefficiency of noncooperative behavior is well known, and is most (in)famously illustrated in classical game theory by ``The Prisoner's Dilemma'' and in network routing by the counterintuitive ``Braess's Paradox''. In this talk, I will discuss methods for quantifying the worst-possible loss in network performance arising from such noncooperative behavior --- the ``price of anarchy''. I will also briefly touch on methods for improving the noncooperative solution, including network design and edge pricing. Host: Professor Anna Lysyanskaya From talks@list.cs.brown.edu Tue Mar 2 22:11:56 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 2 Mar 2004 17:11:56 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Christian Poellabauer in Lubrano on 3/24/04 at noon Message-ID: <20040302221155.736532F077@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Christian Poellabauer Georgia Institute of Technology Wednesday, March 24, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am System Support for the Integrated Management of Quality of Service The increasing number of network-enabled systems and the growing complexity of distributed applications pose numerous challenges for the management and provision of Quality of Service (QoS). Particularly in resource-scarce environments, such as mobile wireless systems, adaptation of applications and system-level resource management are used to provide users with the performance and qualities they need. The distributed management of Quality of Service has been the focus of intensive research efforts and has led to a multitude of techniques at the hardware, network, system, or application layer. However, if multiple such techniques are deployed in a system, an integrated approach to QoS management has to be chosen, to ensure optimal results and to prevent adverse effects resulting from competing techniques. In this talk, I will address how the adaptation of applications and the management of multiple system constraints can be coordinated to efficiently provide users with the QoS they need. This coordination is supported by Q-Fabric, a collection of operating system extensions, which provide the framework to deploy feedback-based integrated QoS management for distributed applications. Specifically, my talk will focus on the integrated approach to distributed energy management for mobile multimedia applications. The goal is to efficiently deploy and coordinate novel energy management techniques at different layers of a system, while carefully balancing the user-perceived QoS with the system's energy consumption. Host: Professor Tom Doeppner From talks@list.cs.brown.edu Wed Mar 3 18:37:03 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 3 Mar 2004 13:37:03 -0500 Subject: [Brown CS Talks] Brown CS Colloquium: Andreas Zeller in Room 368 (CIT 3rd floor) on 3/22/04 at 10:15 am Message-ID: <20040303183703.32CA22F07D@null.cs.brown.edu> BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Andreas Zeller Saarland University Monday, March 22, 2004 at 10:15 am Room 368 (CIT 3rd floor) Why Does My Program Fail? Despite all advances in program analysis, narrowing down failure causes is still a manual task, dependent on the skill and the endurance of the programmer. In this talk, I present some techniques that widely automate the quest for failure causes. Based on a simple trial-and-error process and an automated test, it is fairly simple to isolate external failure causes like input, code differences, or thread schedules. Advanced techniques can even isolate cause-effect chains within the program run: ``First, variable x_1 had a value of x_1, thus v_2 became x_2, thus v_3 was set to x_3 ... and thus the program failed''. Case studies on real programs with real bugs, such as the GNU C compiler, demonstrate the practical feasibility of these experimental approaches. Already today, anyone can submit buggy programs via our ``AskIgor'' web service to obtain failure diagnoses automatically; integration into common programming environments is underway. In the future, user applications may leverage automated diagnosis to become self-diagnosing and even partially self-healing - just by linking in a special diagnosis library. Andreas Zeller is a computer science professor at Saarland University, Saarbruecken, Germany, since 2001. His research concerns the analysis of large software systems and their histories, especially the analysis of why these systems fail to work as they should. Host: Professor Shriram Krishnamurthi From talks@list.cs.brown.edu Thu Mar 4 21:19:51 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 4 Mar 2004 16:19:51 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Douglas Thain in Lubrano on 3/11/04 at noon Message-ID: <20040304211951.C83FB2F003@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Douglas Thain University of Wisconsin Thursday, March 11, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Explicit Control in a Batch-Aware Distributed Filesystem Science and industry rely on large-scale batch computing to solve important strategic problems with brute force. However, batch computing has never sufficiently supported workloads with significant data needs. A conventional but inadequate solution is to couple a stock batch system to a stock distributed filesystem. This approach is limited in scalability and reliability and has forced users to either limit their data needs or distribute data manually. To solve this problem, we introduce a new system structure called the Batch-Aware Distributed Filesystem (BAD-FS). Unlike traditional systems, the components of BAD-FS expose their state and policies to an external scheduler. Using this control, the scheduler allocates and orchestrates a personal, data-intensive computing system on the fly. By moving control from the core to the edge, BAD-FS is able to solve several perennial problems in distributed computing, such as space allocation, consistency management, and the safety-performance tradeoff. We demonstrate the utility of BAD-FS with a suite of five scientific workloads in a controlled local cluster and in a wide-area multi-cluster environment. Host: Professor Steve Reiss From talks@list.cs.brown.edu Thu Mar 4 21:32:45 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 4 Mar 2004 16:32:45 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Dan Klein in Lubrano on 3/15/04 at noon Message-ID: <20040304213242.ACE8D2F009@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Dan Klein Stanford University Monday, March 15, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Unsupervised Learning of Natural Language Structure There is precisely one complete language processing system to date: the human brain. Though there is debate on how much built-in bias human learners might have, we definitely acquire language in a primarily unsupervised fashion. On the other hand, computational approaches to language processing are almost exclusively supervised, relying on hand-labeled corpora for training. This reliance is largely due to repeated failures of unsupervised approaches. In particular, the problem of learning syntax (grammar) from completely unannotated text has received a great deal of attention for well over a decade, with little in the way of positive results. We argue that previous methods for this task have generally failed because of the representations they used. Overly complex models are easily distracted by non-syntactic correlations (such as topical associations), while overly simple models aren't rich enough to capture important first-order properties of language (such as directionality, adjacency, and valence). We describe several syntactic representations which are designed to capture the basic character of natural language syntax as directly as possible. With these representations, high-quality parses can be learned from surprisingly little text, with no labeled examples and no language-specific biases. Our results are the first to show above-baseline performance in unsupervised parsing, and far exceed the baseline (in multiple languages). These specific grammar learning methods are useful since parsed corpora exist for only a small number of languages. More generally, most high-level NLP tasks, such as machine translation and question-answering, lack richly annotated corpora, making unsupervised methods extremely appealing even for common languages like English. Host: Professor Eugene Charniak From talks@list.cs.brown.edu Thu Mar 4 21:33:25 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 4 Mar 2004 16:33:25 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Kevin Murphy in Lubrano on 3/17/04 at noon Message-ID: <20040304213322.3FCC22F009@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Kevin Murphy MIT Wednesday, March 17, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Probabilistic graphical models for scene and object recognition Probabilistic graphical models are a way of combining multiple sources of noisy evidence together in a principled fashion, in order to come up with an optimal estimate of the hidden state of a system. Well-known examples include Kalman filters and HMMs. In this talk, I will show how we can use graphical models to perform fast and robust place and scene recognition. I will then show how to extend the model to detect objects such as cars, people, computers, etc. We use the output of the scene recognition system to decide which objects are likely to be present (for example, cars are unlikely in indoor scenes). Next we use global image features to predict the likely location of the object. Finally we apply a standard object detector (based on boosted decision stumps) to the image. The various sources of information are combined using a discriminatively trained graphical model (a conditional random field). We discuss some methods for efficiently training such models, and demonstrate our system on a challenging dataset of indoor and outdoor images collected with a wearable camera. Host: Professor Michael Black From talks@list.cs.brown.edu Thu Mar 4 21:39:37 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 4 Mar 2004 16:39:37 -0500 Subject: [Brown CS Talks] Brown CS Seminar: David Andersen in Lubrano on 3/23/04 at noon Message-ID: <20040304213950.C48CC2EFDC@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department David Andersen MIT Tuesday, March 23, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Improving the End-to-end Availability of Internet-based Systems The end-to-end availability of Internet services is between two and three orders of magnitude worse than other important engineered systems, including the US airline system, the 911 emergency response system, and the US public telephone system. This talk makes two contributions to improve end-to-end availability. First, a study of three years of data collected on a 31-site testbed explores why failures happen, and finds that access network failures, inter-provider and wide-area routing anomalies, domain name system faults, and server-side failures all have a role to play in reducing availability. Second, an overlay network with new algorithms for end-to-end path selection improves availability by one or two orders of magnitude compared to the current state. A purely overlay-based system, RON (resilient overlay networks), deploys nodes in different organizations and networks, carefully measures and monitors the status of available paths, and relies on them to cooperatively route packets by way of each other to bypass faults. A second system, RAN (resilient access networks), uses a combination of physical path redundancy and overlays within a network of cooperative Web proxies to improve the availability for Web users. Experimental evidence suggests that RON can reduce failures by a factor of six, and that with physical path redundancy, a six-site RAN eliminates almost all network-based failures. Host: Professor John Jannotti From talks@list.cs.brown.edu Tue Mar 9 19:04:24 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 9 Mar 2004 14:04:24 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Meinolf Sellman in Lubrano on 3/22/04 at noon Message-ID: <20040309190436.263FA2EFE4@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Meinolf Sellmann Cornell University Monday, March 22, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Optimality through Approximation A key challenge when devising exact algorithms for NP-hard problems is the identification of tractable subtasks, the most prominent historical example being the computation of linear continuous relaxations. We show how approximation algorithms can be exploited within the computation of exact solutions, first by providing the basis of cost-based filtering algorithms, and second, by quickly approximating a bound on the objective function. Specifically, we devise an amortized linear-time filtering algorithm for Knapsack constraints that eliminates all non-profitable variable assignments with respect to bounds of arbitrary but constant accuracy. Moreover, we present an approximation scheme for Maximum Multicommodity Flows (MMCF) with multiple sinks that is used as a bounding routine within an exact solver for Graph Bisection. We evaluate these theoretical contributions in rigorous numerical experiments in the context of Market Split and Graph Bisection, and show that the new techniques produce significant practical benefits. In particular, Knapsack approximation results in the first standard solution approach that can tackle hard Cornuejols-Dawande instances. Moreover, by approximating MMCFs we were able to close the following open bisection problems: DeBruijn 8, DeBruijn 9, Shuffle-Exchange 9, and Shuffle-Exchange 10. Host: Professor Pascal Van Hentenryck From talks@list.cs.brown.edu Wed Mar 17 18:50:35 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 17 Mar 2004 13:50:35 -0500 Subject: [Brown CS Talks] Brown University Seminar: Ramesh Raskar in Room 190 - Barus & Holley on March 18, 2004 at 1 pm Message-ID: <20040317185035.7D1462EF96@null.cs.brown.edu> SHAPE Lab Seminar BROWN UNIVERSITY Ramesh Raskar MERL Vision, Graphics and HCI Research at MERL Thursday, March 18, 2004 at 1 pm Barus & Holley, Room 190 As computing has moved off the desktop, research in interaction, computer graphics, computer vision and usability has become more interdisciplinary and requires teams of very diverse composition. I will illustrate this point with a brief description of selected projects at MERL. They include algorithms for smart elevators, quantifying presence and flow of people, multi-user touch screens, LED based communication and chemical sensing. I will also describe my group's work in locale-aware mobile projectors, composite RFIDs, image fusion and multi-flash depth-edge detecting camera- for interaction, display and augmentation. (The projects above represent the research efforts of many members of the MERL staff. For appropriate credits, please visit the MERL web site, http://www.merl.com ). Ramesh Raskar joined MERL as a Research Scientist in 2000 after his doctoral research at the University of North Carolina at Chapel Hill, where he developed a framework for projector based displays. Dr. Raskar's work spans a range of topics in computer vision and graphics including projective geometry, non-photorealistic rendering and intelligent user interfaces. He has developed algorithms for image projection on planar, non-planar and quadric curved surfaces that simplify constraints on conventional displays and has proposed Shader Lamps, a new approach for projector-based augmented reality. Current projects include composite RFID, multi-flash non-photorealistic camera for depth edge detection, locale-aware mobile projectors, high dynamic range video, image fusion for context enhancement and quadric transfer methods for multi-projector curved screen displays. Dr. Raskar received the Mitsubishi Electric Information Technology R&D Award in June 2003. Recently, he was named a winner of the Global Indus Technovator Award, instituted at MIT to recognize the top 20 Indian technology innovators on the globe. His papers have appeared in SIGGRAPH, Eurographics, IEEE Visualization, CVPR and many other graphics and vision conferences. He has taught courses and has served as a member of international program committees at major conferences. He is a member of the ACM and IEEE. http://www.merl.com/people/raskar/raskar.html From talks@list.cs.brown.edu Thu Mar 25 21:56:34 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 25 Mar 2004 16:56:34 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Derek Jones in Lubrano on 4/1/04 at noon Message-ID: <20040325215633.66DB72F021@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_0084_01C4128A.211927A0 Content-Type: text/plain; charset="US-ASCII" Content-Transfer-Encoding: 7bit The Department of Computer Science BROWN UNIVERISTY Derek Jones NIH Thursday, April 1, 2004 at noon Lubrano Conference Room, (CIT 4th floor) Refreshments will be served at 11:45 am "Diffusion MRI tractography and its quantitative use in schizophrenia research" Host: Professor David Laidlaw ------=_NextPart_000_0084_01C4128A.211927A0 Content-Type: text/html; charset="US-ASCII" Content-Transfer-Encoding: quoted-printable

The Department of = Computer Science

 

 

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“Diffusion MRI tractography and its quantitative use in

schizophrenia research”

 

 

 

 

Host: Professor David Laidlaw

 

 

 

 

 

 

------=_NextPart_000_0084_01C4128A.211927A0-- From talks@list.cs.brown.edu Tue Mar 30 18:12:27 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 30 Mar 2004 13:12:27 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Adam Klivans in Lubrano on 4/7/04 at noon Message-ID: <20040330181223.C558A3CFF@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Adam Klivans Harvard University Wednesday, April 7, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Learning Halfspaces: New Algorithms and Applications Learning a halfspace is one of the oldest and most fundamental tasks in machine learning. It is the essential underlying algorithm for many systems used for classifying data by practitioners from fields such as artificial intelligence, statistics, and computational biology. In this talk we will give several new approaches for learning halfspaces and describe surprising algorithmic applications. First, we will show that learning a halfspace in high dimensions yields fast algorithms for learning Boolean concept classes such as DNF formulae, one of the major challenges in computational learning theory. To this end we will show how to obtain the fastest known DNF learning algorithm. Secondly, we will describe two new algorithms for learning intersections of halfspaces. Intersections of halfspaces are a powerful concept class; any convex body can be expressed as an intersection of halfspaces, and little is known about the complexity of learning the intersection of even two halfspaces. We give the first polynomial-time algorithms for learning the intersection of any constant number of halfspaces assuming either a margin separating positive points from negative points or that the points are chosen uniformly at random. Host: Professor John Savage From talks@list.cs.brown.edu Thu Apr 8 20:07:26 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 8 Apr 2004 15:07:26 -0400 Subject: [Brown CS Talks] Brown CS Colloquium: Gregg Rothermel in Lubrano on 4/15/04 at 4 pm Message-ID: <20040408190730.386833D2B@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Gregg Rothermel Oregon State University Thursday, April 15, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Software Testing: An Evolution-Centric Perspective Useful software evolves: it is corrected, enhanced, and adapted to new platforms, resulting in new releases of systems. To validate these new releases, software engineers ``regression test'' them. Such regression testing is important for software quality, but it is also expensive, and in fact, often dominates overall software costs. This motivates an evolution-centric perspective on software testing, where emphasis is placed on regression testing. In this talk I describe research following this perspective. I first describe one particular approach to regression testing using regression test selection techniques (which reduce regression testing costs by selecting subsets of existing test suites for reexecution), present techniques for performing regression test selection, and describe empirical results obtained in studying those techniques. I then summarize other recent research on evolution-centric testing, including test case prioritization, and discuss ramifications of that work. Host: Manos Renieris From talks@list.cs.brown.edu Wed Apr 14 21:36:32 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 14 Apr 2004 16:36:32 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Thomas Raedler in Lubrano on 4/27/04 at noon Message-ID: <20040414203606.8397E3CFB@null.cs.brown.edu> Computer Science - Department of Psychiatry and Human Behavior Seminar BROWN UNIVERSITY Thomas Raedler University of Hamburg Tuesday, April 27, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am White matter changes in OCD Introduction: While the etiology of obsessive-compulsive disorder (OCD) remains unclear, a dysregulation in the fronto-striato-thalamic circuitry has been postulated. Diffusion Tensor Imaging (DTI), a newly developed non-invasive magnetic resonance imaging method, has made it possible to study fiber tracts in the living human brain. Method: 17 subjects with a primary diagnosis of OCD underwent a 40-minute DTI-scan on a Siemens Magnetom Vision 1.5 T MR scanner. 21 age- and sex-matched healthy volunteers served as a control-group. The image-analysis was performed in SPM99. Results: At a significance-level of p < 0.05, we found wide-spread reductions of the fractional anisotropy in OCD in the left hemisphere. These changes include projections between frontal cortex, basal ganglia, thalamus and temporal cortex. At a significance-level of p < 0.001, fractional anisotropy was diminished in an area of the right mediofrontal cortex. Conclusions: This is the first in-vivo study to date of the white matter in OCD. Our results suggest wide-spread changes in the white matter in OCD affecting primarily the left hemisphere. Hosts: Professor David Laidlaw and Benjamin Greenberg From talks@list.cs.brown.edu Wed Apr 14 21:37:40 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 14 Apr 2004 16:37:40 -0400 Subject: [Brown CS Talks] Brown CS Colloquium: Scott Smolka in Lubrano on 4/29/04 at 4 pm Message-ID: <20040414203714.CC0D23D02@null.cs.brown.edu> BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Scott Smolka SUNY Stony Brook Thursday, April 29, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Monte Carlo Model Checking We present what we believe to be the first randomized Monte Carlo algorithm for model checking, the problem of deciding whether or not a property specified in temporal logic holds of a system specification. Given an \epsilon, \delta, system S succinctly specified using Reactive Modules, and a Linear Temporal Logic (LTL) formula \phi, our algorithm produces an estimate of the probability that S satisfies \phi within a factor of 1 + \epsilon with probability at least 1 - \delta. It does so using a number of samples N that is optimal to within a constant factor, and in expected time linear in N \cdot |S| \cdot 2^{|\phi|}. Joint work with Radu Grosu. Host: Professor Tom Doeppner From talks@list.cs.brown.edu Thu Apr 15 20:41:53 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 15 Apr 2004 15:41:53 -0400 Subject: [Brown CS Talks] [Brown CS Distinguished Lecture] Robert Schapire Message-ID: <20040415194154.814963D0E@null.cs.brown.edu> 25th ANNIVERSARY DISTINGUISHED LECTURE Modern Approaches to Machine Learning 4pm Thursday, April 22, 2004 Lubrano Conference Room Robert Schapire '86 Princeton University This talk will focus on a general-purpose machine-learning method called boosting. The main idea of this method is to produce a very accurate classification rule by combining rough and moderately inaccurate "rules of thumb." While rooted in a theoretical framework of machine learning, boosting has been found to perform quite well empirically. In this talk, I will introduce the boosting algorithm AdaBoost, and explain the underlying theory of boosting, including our explanation of why boosting often does not suffer from overfitting, as well as some of the myriad other theoretical points of view that have been taken on this single algorithm. I also will describe some recent applications of boosting. Host: Professor Philip Klein There will be a reception following the talk. From talks@list.cs.brown.edu Tue Apr 20 20:16:29 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 20 Apr 2004 15:16:29 -0400 Subject: [Brown CS Talks] Brown CS Theory Colloquium: Lisa Fleischer in Lubrano on April 28, 2004 at 4 pm Message-ID: <20040420191629.9B6AB3D26@null.cs.brown.edu> BROWN UNIVERSITY THEORY COLLOQUIUM Lisa Fleischer IBM T. J. Watson Wednesday, April 28, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Taxes for heterogeneous, selfish users of a multicommodity network We prove the existence of taxes to induce multicommodity, heterogeneous network users that independently choose routes minimizing their own linear function of taxes versus latency to collectively form the traffic pattern of a minimum average latency flow. Unlike previous proofs for single commodity users in general graphs, our proof is constructive - it does not rely on a fixed point theorem - and results in a simple polynomial-sized linear program to compute taxes when the number of different types of users is bounded by a polynomial. We give a complete characterization of flows that are enforceable by taxes. Thus, taxes exist to minimize average weighted latency flows, maximum latency flows, and other natural objectives. For single commodity traffic, we prove that taxes that are linear in the size of the network are sufficient to induce enforceable congestions. Finally, we show that our result extends to handle general nonatomic congestion games. In particular, taxes exist even when 1) latencies depend on user type; 2) latency functions are nonseparable functions of traffic on edges; 3) the latency of a set S is an arbitrary function of the latencies of the resources contained in S. This is joint work with Kamal Jain of Microsoft Research and Mohammad Mahdian of MIT. Host: Professor Philip Klein From talks@list.cs.brown.edu Tue Apr 20 20:25:38 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 20 Apr 2004 15:25:38 -0400 Subject: [Brown CS Talks] Brown CS Theory Colloquium: Leonid Reyzin in Lubrano on May 12, 2004 at 4 pm Message-ID: <20040420192538.D5F6B3D2E@null.cs.brown.edu> BROWN UNIVERSITY THEORY COLLOQUIUM Leonid Reyzin Boston University Wednesday, May 12, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data We provide formal definitions and efficient secure techniques for -- turning biometric information into keys usable for any cryptographic application, and -- reliably and securely authenticating biometric data. Our techniques apply not just to biometric information, but to any keying material that, unlike traditional cryptographic keys, is (1) not reproducible precisely and (2) not distributed uniformly. We propose two primitives: a fuzzy extractor extracts nearly uniform randomness R from its biometric input; the extraction is error-tolerant in the sense that R will be the same even if the input changes, as long as it remains reasonably close to the original. Thus, R can be used as a key in any cryptographic application. A secure sketch produces public information about its biometric input w that does not reveal w, and yet allows exact recovery of w given another value that is close to w. Thus, it can be used to reliably reproduce error-prone biometric inputs without incurring the security risk inherent in storing them. In addition to formally introducing our new primitives, we provide nearly optimal constructions of both primitives for various measures of ``closeness'' of input data, such as Hamming distance, edit distance, and set difference. Joint work with Yevgeniy Dodis (NYU) and Adam Smith (MIT) Host: Professor Anna Lysyanskaya From talks@list.cs.brown.edu Wed Apr 21 18:56:08 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 21 Apr 2004 13:56:08 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Justin Boyan in Lubrano on April 22, 2004 at 10:30 am Message-ID: <20040421175609.0B4523D1A@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Justin Boyan ITA Software Thursday, April 22, 2004 at 10:30 am Lubrano Conference Room (CIT 4th floor) AI in the Real World: Air Travel Planning What goes on behind the scenes when you search for airfares on sites like Orbitz and Continental.com? As it turns out, a whole lot of sophisticated computer science. The combinatorics of airfare search are daunting. There are 25,000,000 practical flight combinations for a round-trip between Boston and Los Angeles with one-day travel windows. Computing the price for any one of those ways is at least NP-hard. Fares are updated five times a day, while seat availability data is updated in real-time at 100Hz. In this talk, we'll discuss how airfare pricing really works, how AI algorithms can be applied to the problem, and how those algorithms have propelled a small company to success. Host: Professor Amy Greenwald From talks@list.cs.brown.edu Tue Apr 27 21:48:58 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 27 Apr 2004 16:48:58 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Mel Slater in Lubrano on May 5, 2004 at 4 pm Message-ID: <20040427204858.499E73D3F@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Mel Slater Dept. of Computer Science, University College London Wednesday, May 5, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Presence in Virtual Environments This talk will introduce the concept of presence in virtual environments - usually defined as the ``sense of being there'' in the environment depicted by the virtual reality display systems. Various methods of measurement including questionnaires, behavioral and physiological measures will be discussed, together with a discussion of some recently completed experiments involving interactions with virtual characters. Results from applications in the realm of psychotherapy will be presented. Host: Professor Andy van Dam From talks@list.cs.brown.edu Tue Apr 27 21:49:55 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 27 Apr 2004 16:49:55 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Jim Thomas and Richard May in Lubrano on May 6, 2004 at 4 pm Message-ID: <20040427204955.9206F3D3F@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Jim Thomas and Richard May Pacific Northwest National Laboratory (PNNL) Thursday, May 6, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Visual Analytics and the National Research Agenda Jim Thomas will discuss the current state of visual analytics and its importance to national security. The on-going development of a national visual analytics center and research opportunities available through the center will be outlined. Directly Mediated Interaction: HI-SPACE and the Mouse Richard May will discuss the ideals of directly mediated computer interaction and introduce the Human Information Workspace (HI-SPACE), a technology designed to support and investigate these ideals. The results of a series of usability studies will be presented that compare performance characteristics of directly mediated interaction to that of the mouse for simple target acquisition. Host: Professor Andy van Dam From talks@list.cs.brown.edu Mon May 3 20:18:45 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Mon, 3 May 2004 15:18:45 -0400 Subject: [Brown CS Talks] BROWN CS SPECIAL COLLOQUIUM: Maurice Herlihy in Lubrano on May 11, 2004 at 4 pm Message-ID: <20040503191849.9C3833C94@null.cs.brown.edu> BROWN UNIVERSITY COMPUTER SCIENCE SPECIAL COLLOQUIUM Maurice Herlihy Brown Computer Science Tuesday, May 11, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Algebraic Topology and Distributed Computing Models and techniques borrowed from classical algebraic topology have yielded a variety of new results for wait-free distributed computing. This talk will survey the basic concepts underlying this approach, and will show how they apply to a simple distributed problem. This talk is self-contained, and is intended for a general audience. Host: Professor Franco Preparata From talks@list.cs.brown.edu Tue Jun 22 20:28:47 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 22 Jun 2004 15:28:47 -0400 Subject: [Brown CS Talks] Brown CS Thesis Defense: Don Carney in Lubrano on June 30, 2004 at 10 am. Message-ID: <20040622192746.90E9E3CF6@null.cs.brown.edu> BROWN UNIVERSITY Computer Science Department Don Carney Thesis Defense Wednesday, June 30, 2004 at 10 am Lubrano Conference Room (CIT 4th floor) Application-Aware Resource Scheduling The proliferation of the Internet and World Wide Web, the development of wireless networks, the availability of asymmetric high-bandwidth links to the home, and the recent emergence of small-scale computing devices have fueled the development of applications with wide and varied data needs. The data-intensive environments in which these applications exist are characterized by very high data rates, the scale and variety of autonomous data sources, and the diverse needs of users and applications. Often, the resources (memory, bandwidth, etc.) in these environments are constrained and data management plays an important role in providing fast responsive systems through the effective scheduling of resources. Databases have long benefited from the use of application-level knowledge to make decisions. For example, database indices are built on attributes that are known to be commonly used. Often, this application-level awareness comes from a priori knowledge of user interests. In these new networked environments there is evidence that more responsive systems can be delivered if users provide either some general indication of their interest or even better, a detailed query. We call this specification of user interest a ``profile''. This dissertation focuses on two applications domains. In the first application domain, the process of synchronizing a database to improve the freshness of copies is studied. In the second application domain, we study the timely processing of large volumes of continuous high-rate data streams in the context of the Aurora data stream manager. In both cases, profiles show promise in improving resource scheduling to provide effective data management. Host: Professor Stan Zdonik From talks@list.cs.brown.edu Thu Jun 24 16:20:36 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 24 Jun 2004 11:20:36 -0400 Subject: [Brown CS Talks] Brown CS Colloquium: Tevfik Bultan in Lubrano on 7/9/04 at 2 pm Message-ID: <20040624152026.AD2E03CF4@null.cs.brown.edu> BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Tevfik Bultan University of California Friday, July 9 2004 at 2 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 1:45 pm Tools for Automated Verification of Web services Web Service Analysis Tool (WSAT) analyzes interactions of web services that communicate with asynchronous messages. We model the interactions in such a system as a conversation, the global sequence of messages that are exchanged among the web services. A conversation protocol is an automaton which specifies a set of conversations. There are two interesting properties within this framework: realizability and synchronizability. A conversation protocol is realizable if the corresponding conversation set can be generated by a set of asynchronously communicating web services. On the other hand, a set of asynchronously communicating web services are synchronizable if their conversation set does not change when asynchronous communication is replaced with synchronous communication. WSAT verifies LTL properties of conversation protocols and checks sufficient conditions for realizability and synchronizability. In order to model XML data, WSAT uses a guarded automata model where the guards of the transitions are written as XPath expressions. Currently, WSAT uses the explicit-state model checker SPIN for LTL model checking by translating the guarded automata model to Promela. In the future, we plan to use Action Language Verifier for symbolic analysis and verification of web services. Action Language Verifier is an infinite state model checker for concurrent systems. It combines different symbolic representations, such as BDDs for boolean logic formulas and polyhedral and automata based representations for linear arithmetic formulas. BIO: Tevfik Bultan received his B.S. in electrical and electronics engineering in 1989 from the Middle East Technical University, and his M.S. in computer engineering and information science in 1992 from the Bilkent University, both in Ankara, Turkey. He received his Ph.D. in computer science in 1998 from the University of Maryland, College Park. He joined the Computer Science Department of the University of California, Santa Barbara in September 1998. Tevfik Bultan received a NATO Science Fellowship from the Scientific and Technical Research Council of Turkey (TUBITAK) in 1993, a Regents' Junior Faculty Fellowship from the University of California, Santa Barbara in 1999, and a Faculty Early Career Development (CAREER) Award from the National Science Foundation in 2000. Tevfik Bultan's current research interests are: web services, concurrency, model checking, static analysis, and software engineering. Host: Professor Shriram Krishnamurthi From talks@list.cs.brown.edu Thu Jul 15 17:04:12 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 15 Jul 2004 12:04:12 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Andrew Fitzgibbon in Lubrano on 7/30/04 at 3 pm Message-ID: <20040715160436.821E73D19@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_001C_01C46A63.D7B13D00 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit Vision and Learning Seminar Series BROWN UNIVERSITY Computer Science Department Andrew Fitzgibbon New College, Oxford University Friday, July 30, 2004 at 3 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 2:45 pm Applied natural image statistics for computer vision I shall describe recent work on the regularization of certain inverse problems in computer vision using natural image statistics. I shall look first at the problem of multiview stereo reconstruction recast as image-based rendering. We show results which are the current state of the art, and which are significant improvements over other techniques. The second problem is layer extraction with subpixel accuracy, again a difficult inverse problem, for which good priors/regularizers are essential if a useful solution is to be obtained. I will show examples of how this sort of work applies to the demanding problems of generating realistic cinematic special effects. Host: Professor Michael Black ------=_NextPart_000_001C_01C46A63.D7B13D00 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

Vision and = Learning Seminar Series

 

BROWN UNIVERSITY

Computer Science = Department

 

 

 

Andrew = Fitzgibbon

 

New College, = Oxford University

 

Friday, July 30, = 2004 at 3 pm

Lubrano Conference = Room (CIT 4th floor)

Refreshments will = be served at 2:45 pm

 

Applied natural = image statistics for computer vision

 

 

I shall describe recent work on the regularization of certain = inverse

problems in computer vision using natural image = statistics.  I shall

look first at the problem of multiview stereo reconstruction = recast as

image-based rendering.  We show results which are the = current state of

the art, and which are significant improvements over other = techniques.

The second problem is layer extraction with subpixel accuracy, = again a

difficult inverse problem, for which good priors/regularizers = are

essential if a useful solution is to be obtained.  I will = show

examples of how this sort of work applies to the demanding = problems of

generating realistic cinematic special = effects.

 

Host: Professor = Michael Black

------=_NextPart_000_001C_01C46A63.D7B13D00-- From talks@list.cs.brown.edu Wed Aug 4 19:10:55 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 4 Aug 2004 14:10:55 -0400 Subject: [Brown CS Talks] Brown CS Thesis Defense: Keith Hall in Lubrano on 8/13/04 at 11 am Message-ID: <20040804181059.5488644C014@null.cs.brown.edu> BROWN UNIVERSITY Computer Science Department Keith Hall Thesis Defense Friday, August 13, 2004 at 11 am Lubrano Conference Room (CIT 4th floor) Best-first Word-lattice Parsing: Techniques for integrated syntactic language modeling Natural language processes such as speech recognition and translation are typically modeled as a noisy channel. Under the noisy channel model the task of inference is divided into two components: the noise model, responsible for assigning probability to an observed signal given a word-string; and the language model, responsible for assigning probability to hypothetical word-strings. The n-gram, a linear Markov chain model over the words in a string, has been the standard language model for such tasks. Recent work on syntactic language models shows that by incorporating syntactic structure into the model, performance is improved over the standard n-gram approach (in particular, the trigram). In this work we introduce a language modeling technique based on statistical parsing. Unlike previous techniques, our parsing model performs syntactic analysis on sets of hypothesized word-strings (encoded as word-lattices) simultaneously. We employ a best-first search approach that directs the parser towards good parses as well as good word-strings (according to a probabilistic context-free grammar). We describe the best-first heuristic function that drives this search. This word-lattice parsing model is combined with the Charniak language model to provide a complete word-lattice syntactic language modeling technique. Additionally, we discuss modifications to the parsing algorithm as well as alternative heuristic functions for richer non-context-free grammars (specifically a lexicalized PCFG). We present experimental results for these techniques as applied to speech recognition. The results show that our technique performs with the same accuracy as n-best list rescoring techniques and is capable of reducing the amount of work required to achieve these results. Finally, we suggest that the structure of our model provides a flexible environment for experimenting with alternative parsing heuristics which may be directed towards objectives other than the maximum likelihood parse. Host: Professor Mark Johnson From talks@list.cs.brown.edu Wed Sep 1 15:13:23 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 1 Sep 2004 10:13:23 -0400 Subject: [Brown CS Talks] Wayland Seminar Series, Sept. 14th, Roberto Serrano Message-ID: <20040901141323.1F06944C002@null.cs.brown.edu> The Wayland Collegium Faculty Interdisciplinary Seminar Series on Decision Making & Rationality presents Roberto Serrano Department of Economics September 14, 2004, 4PM Lubrano Conference Room (CIT 4th floor 115 Waterman Street Refreshments will be served at 3:45 Rejecting Small Gambles Under Expected Utility: A Recent Controversy Abstract: A recent literature (e.g., Rabin (2000), Rabin and Thaler (2001)) concludes that expected utility theory is fundamentally unfit to explain decisions under uncertainty. The claim is based on a theorem establishing the relationship between behavior towards small-stakes and large-stakes gambles. In particular, it is shown there that if an expected utility maximizer were to reject a small gamble over a range of wealth levels, he would paradoxically reject extremely favorable large gambles. The authors appeal to introspection to justify the reasonableness of the ``rejecting small gambles'' assumption, thereby reaching their conclusion: the decision maker cannot possibly be maximizing expected utility. Our starting point is to point out that rejecting a gamble over a given range of wealth levels imposes a lower bound on risk aversion. Comparing the lower bound on risk aversion implied by Rabin's thought experiments to empirical evidence on how decision makers really behave in many real-life circumstances involving risk, we conclude that the levels of risk aversion implied by Rabin's introspection exercises are unrealistically high. It follows that expected utility is not at fault, and the explanation for the paradoxical behavior found in the rejection of large gambles can be attributed to his assumption of rejecting small gambles over too big a range of wealth levels. Finally, if we impose the ``rejecting small gambles'' assumption over a range of wealth levels consistent with the empirical evidence, paradoxical rejections of large gambles are no longer found. **************************** Fran Palazzo Administrative Assistant Computer Science Department Brown University 115 Waterman Street - 546 Box 1910 Providence, RI 02912 401-863-7611 fp@cs.brown.edu From talks@list.cs.brown.edu Wed Sep 1 15:19:45 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 1 Sep 2004 10:19:45 -0400 Subject: [Brown CS Talks] Wayland Seminar Series, Steven Sloman, Sept 28th, 4pm Message-ID: <20040901141945.7603444C004@null.cs.brown.edu> Seminar BROWN UNIVERSITY The Wayland Collegium Faculty Interdisciplinary Seminar Series on Decision Making & Rationality presents Steven Sloman Department of Cognitive & Linguistic Science Tuesday, September 28, 2004, 4PM Lubrano Conference Room (CIT 4th floor 115 Waterman Street Refreshments will be served at 3:45 Decision-making and the Causal World: Choice as Intervention I'll present a concise overview of the psychology of judgment and decision making, focusing on the work of Kahneman and Tversky, and then turn to the role of causal models in choice. A framework for reasoning about causality has been developed by Spirtes, Glymour, and Scheines (1993) and is reviewed in Pearl (2000). The fundamental idea is that people represent the world by decomposing it into autonomous causal mechanisms that support interventions. On this view, human reasoning is understood as a tool to support human action. The application of the ideas to decision making reveals that good decisions depend on causal analysis and that choice is a form of intervention. I describe a couple of experimental tests of whether people's choices conform to these constraints. **************************** Fran Palazzo Administrative Assistant Computer Science Department Brown University 115 Waterman Street - 546 Box 1910 Providence, RI 02912 401-863-7611 fp@cs.brown.edu From talks@list.cs.brown.edu Fri Sep 10 20:58:39 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Fri, 10 Sep 2004 15:58:39 -0400 Subject: [Brown CS Talks] Brown CS Colloquium: Mike Sperber in Lubrano on 9/16/04 at 4 pm Message-ID: <20040910195839.2CB1444C004@null.cs.brown.edu> BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Mike Sperber DeinProgramm Thursday, September 16, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Object-Oriented Programming Considered Harmful When prescribing how to solve a problem, object-oriented analysis, design, and programming teach us to translate the world of the problem into the world of classes, methods, and mutable objects. Unfortunately, not all problems readily lend themselves to such a translation. Consequently, many object-oriented programs contain mismatches between the natural mental model for an entity in the problem solution and its representation in the code. Object-oriented programmers have accepted this rift as natural and necessary. It is not. Frequently, this merely leads to awkward and hard-to-understand code. Sometimes, however, this practice is outright dangerous, leading to incorrect implementation models that are very difficult to rectify once the programmer has made them. This talk will be an anecdotal rant on the subject, and will showcase the problem (along with a better, non-object-oriented solution) by discussing real-world models for financial market data. Host: Professor Shriram Krishnamurthi From talks@list.cs.brown.edu Mon Sep 13 14:49:12 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Mon, 13 Sep 2004 09:49:12 -0400 Subject: [Brown CS Talks] Brown CS Colloquium: Dina Q. Goldin in Lubrano on 9/23/04 at 4 pm Message-ID: <20040913134912.D70A044C005@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_007F_01C49976.ECB03CA0 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Dina Q. Goldin University of Connecticut Thursday, September 23, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Interaction: Conjectures, Results, and Myths Computer technology has shifted from mainframes to locally networked workstations and now to mobile internet-based computing devices. Software engineering has evolved from procedure-oriented to object-oriented and component-based systems. AI has refocused from logical reasoning and search algorithms to agent-oriented and distributed behaviors. These parallel changes exemplify a conceptual paradigm shift from algorithms to interaction. Interactive computational processes allow for input and output to take place during the computation, in contrast to the traditional ``algorithmic'' models of computation which transform a predefined input into output. Though interaction is an intuitively obvious idea, there has been no domain-independent formalization of interactive computation until now. We introduce Persistent Turing Machines (PTMs), which serve as a model for sequential interactive computation, and allow us to explore the expressiveness of interactive computation. PTMs are multitape Turing Machines (TMs) with a persistent internal tape, and stream-based semantics. We formulate observation-based notions of system equivalence and computational expressiveness, and apply them to demonstrate that PTMs are more expressive than TMs, thus proving Wegner's conjecture that ``interaction is more powerful than algorithms''. We end on a light note by considering the historic reasons for the ``Turing Thesis Myth'', which states that TMs model all computation. This claim, incorrectly reinterpreting the Turing Thesis, is fundamental to the main-stream theory of computation. We show how this myth can be traced to the establishment of computer science as a separate discipline in the 1960's. Host: Professor Peter Wegner ------=_NextPart_000_007F_01C49976.ECB03CA0 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

           = ;          BROWN = UNIVERSITY

 

  = ;          =      COMPUTER SCIENCE COLLOQUIUM

 

           = ;           Dina Q. = Goldin

           = ;            

           = ;       University of Connecticut

 

 

           = ;  Thursday, September 23, 2004 at 4 pm

 

      =        Lubrano Conference Room (CIT 4th floor)

 

           = ; Refreshments will be served at 3:45 pm

 

 

           Interaction: Conjectures, Results, and = Myths

 

Computer technology has shifted from mainframes to locally = networked

workstations and now to mobile internet-based computing = devices.

Software engineering has evolved from procedure-oriented = to

object-oriented and component-based systems.  AI has = refocused from

logical reasoning and search algorithms to agent-oriented = and

distributed behaviors. These parallel changes exemplify a = conceptual

paradigm shift from algorithms to interaction. = Interactive

computational processes allow for input and output to take = place

during the computation, in contrast to the traditional = ``algorithmic''

models of computation which transform a predefined input into = output.

 

Though interaction is an intuitively obvious idea, there has = been no

domain-independent formalization of interactive computation = until now.

We introduce Persistent Turing Machines (PTMs), which serve as a = model

for sequential interactive computation, and allow us to explore = the

expressiveness of interactive computation.  PTMs are = multitape Turing

Machines (TMs) with a persistent internal tape, and = stream-based

semantics.  We formulate observation-based notions of = system

equivalence and computational expressiveness, and apply them = to

demonstrate that PTMs are more expressive than TMs, thus = proving

Wegner's conjecture that ``interaction is more powerful = than

algorithms''.

 

We end on a light note by considering the historic reasons for = the

``Turing Thesis Myth'', which states that TMs model all = computation.

This claim, incorrectly reinterpreting the Turing Thesis, = is

fundamental to the main-stream theory of computation.  We = show how

this myth can be traced to the establishment of computer science = as a

separate discipline in the 1960's.

 

 

           = ;      Host: Professor Peter = Wegner

------=_NextPart_000_007F_01C49976.ECB03CA0-- From talks@list.cs.brown.edu Fri Sep 17 14:31:27 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Fri, 17 Sep 2004 09:31:27 -0400 Subject: [Brown CS Talks] Brown CS Colloquium: Ion Muslea in Lubrano on 9/30/04 at 4 pm Message-ID: <20040917133127.A9C2D44C005@null.cs.brown.edu> BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Ion Muslea SRI Thursday, September 30, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Active Learning with Multiple Views Despite the practical success of machine learning in many real world domains, labeling the training data is time consuming, tedious, and error prone. In this talk, I focus on reducing the need for labeled data in multi-view learning tasks. The key characteristic of multi-view tasks is that the target concept can be independently learned within different views (i.e., disjoint sets of features that are sufficient to learn a concept). For instance, a robot can avoid obstacles based on sonar, laser, or vision sensors; similarly, a Web page can be classified either based on the words in the document or based on the words in the HTML hyperlinks pointing to it. In order to reduce the need for labeled data, I use active learning algorithms that detect and ask the user to label only the most informative examples in a domain. I introduce a family of multi-view active learners that are based on the idea of learning from mistakes. More precisely, they query examples on which the views predict a different label: if two views disagree, one of them is guaranteed to make a mistake. I also show that existing multi-view learners perform unreliably if the views are inadequate. To cope with this problem, I introduce two complementary solutions. First, by interleaving bootstrapping and active learning, I obtain a novel multi-view learner that has a robust behavior over a wide spectrum of domains that have inadequate views. Second, I introduce a meta-learning algorithm that is first trained on several solved learning tasks and then predicts whether or not the views are ``sufficiently adequate'' for solving a new, unseen learning task. I evaluate these three novel algorithms on a variety of real-world domains, from information extraction and text classification to advertisement removal and discourse tree parsing. The empirical results show that my algorithms consistently outperform existing state-of-the-art learners. Ion Muslea received his B.Sc. and M.Sc. in Computer Science from the Technical University of Cluj-Napoca (Romania) and West Virginia University, respectively. In 2002, he received his Ph.D. in Computer Science from the University of Southern California. Upon completing his Ph.D., Ion spend six months as a post-doctoral fellow at U.C. Irvine, after which he joined SRI International's AI Center as a Research Scientist. Ion has done research in machine learning, information extraction, information integration, and AI planning. Host: Professor Chad Jenkins From talks@list.cs.brown.edu Wed Sep 22 13:48:46 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 22 Sep 2004 08:48:46 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Joshua Goodman in Lubrano on 10/7/04 at 4 pm Message-ID: <20040922124846.0397744C00A@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Joshua Goodman Microsoft Thursday, October 7, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Stopping Spam Spam is a huge and growing problem. I'll first survey solutions to spam, including filtering approaches (machine learning, fuzzy hashing, and blackhole lists) and ``postage'' approaches, including reverse Turing tests, computational puzzles, and monetary challenges. Our favorite technique is a machine learning/text classification approach combined with a challenge/response postage approach. I'll talk about problems and solutions we've had in practice, especially how we have gotten millions of messages of labeled training data, both good and spam. I'll also talk briefly about my research on personalizing spam filters, which turns out to be important, but harder than we thought. I'll show some analyses of those millions of messages, including where spam actually comes from, and why legal solutions can only stop a fraction of spam. Next, I'll talk about why email in general and spam in particular need their own new field, combining aspects of machine learning, networking, cryptography/security, HCI, and economics. Joint work with Geoff Hulten, Robert Rounthwaite, David Heckerman, and others. Bio: Joshua Goodman started his professional life as a developer at Dragon Systems, working on speech recognition. He then went to grad school at Harvard University, receiving a Ph.D. for his work in statistical natural language processing, especially statistical parsing. From there, he went to Microsoft Research, where he worked on language modeling. For the past 2 and a half years, he has been working on stopping spam, including helping start Microsoft's Anti-Spam Technology Group. He is General Chair for the Conference on Email and Anti-Spam 2005, which everyone should attend. Host: Professor Eugene Charniak From talks@list.cs.brown.edu Tue Sep 28 14:37:58 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 28 Sep 2004 09:37:58 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Tony DeRose in Lubrano on October 6, 2004 at noon Message-ID: <20040928133758.7FD5F44C003@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Tony DeRose Pixar Wednesday, October 6, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am Math in the Movies Film making is undergoing a digital revolution brought on by advances in areas such as computer technology, computational physics and computer graphics. This talk will provide a behind the scenes look at how fully digital films --- such as Pixar's ``Monsters, Inc.'' and ``Finding Nemo''--- are made, with particular emphasis on the role that mathematics plays in the revolution. Host: Professor John Hughes From talks@list.cs.brown.edu Thu Sep 30 21:16:09 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 30 Sep 2004 16:16:09 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Tony DeRose in MacMillan, Room 115 on 10/6/04 at noon Message-ID: <20040930201609.023E644C002@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_001F_01C4A708.CB962C10 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit Please note Tony DeRose's talk for October 6, 2004 at noon has been moved from Lubrano to MacMillan, Room 115. Seminar BROWN UNIVERSITY Computer Science Department Tony DeRose Pixar Wednesday, October 6, 2004 at noon MacMillan, Room 115 Refreshments will be served at 11:45 am Math in the Movies Film making is undergoing a digital revolution brought on by advances in areas such as computer technology, computational physics and computer graphics. This talk will provide a behind the scenes look at how fully digital films --- such as Pixar's ``Monsters, Inc.'' and ``Finding Nemo''--- are made, with particular emphasis on the role that mathematics plays in the revolution. Host: Professor John Hughes ------=_NextPart_000_001F_01C4A708.CB962C10 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

Please note Tony DeRose’s talk for October 6, 2004 at noon = has been moved from Lubrano to MacMillan, Room 115.

 

 

           = ;            

           = ;            =    Seminar

           = ;         

           = ;          BROWN UNIVERSITY

           = ;      Computer Science Department

           = ;            

           = ;           

           = ;            Tony = DeRose

 

     = ;            =          Pixar

 

 

           = ;   Wednesday, October 6, 2004 at noon

 

           = ;          MacMillan, Room 115

 

      =        Refreshments will be served at 11:45 am

 

 

           = ;           Math in the = Movies

 

 

Film making is undergoing a digital revolution brought on by = advances

in areas such as computer technology, computational physics = and

computer graphics. This talk will provide a behind the scenes = look at

how fully digital films --- such as Pixar's ``Monsters, Inc.'' = and

``Finding Nemo''--- are made, with particular emphasis on the = role

that mathematics plays in the revolution.

 

           = ;            =

           = ;      Host: Professor = John Hughes

 

 

 

------=_NextPart_000_001F_01C4A708.CB962C10-- From talks@list.cs.brown.edu Thu Sep 30 21:16:44 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 30 Sep 2004 16:16:44 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Pedro Dal Bo in Lubrano on 10/12/04 at 4 pm Message-ID: <20040930201644.9297344C002@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_0023_01C4A708.E0CFFAC0 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit The Wayland Collegium Faculty Interdisciplinary Seminar Series on Decision Making & Rationality Pedro Dal Bo Brown University Department of Economics Tuesday, October 12, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Cooperation Under the Shadow of the Future: Experimental Evidence from Infinitely Repeated Games The tension between private incentives that encourage opportunistic behavior and the common good that comes from cooperation is a central feature of human interaction. The main contribution of game theory to the study of this tension and its remedies is to recognize that repeated interaction may enable punishment and reward schemes that prevent or limit opportunistic behavior and support cooperation. When there is always a future, as in infinitely repeated games, the credible threat of future retaliation casts ``the shadow of the future'' in every decision and can overcome opportunistic behavior and support cooperation, thereby solving the tension between private incentives and the common good. However, the experimental evidence on infinitely repeated games is scarce and in most cases inconclusive or presents methodological problems. In this talk I report on a series of experiments that overcome some of the shortcomings of previous experiments on infinitely repeated games. I find that the possibility of future interaction modifies players' behavior resulting in fewer opportunistic actions and supporting cooperation, closely following theoretical predictions. Host: Professor Amy Greenwald ------=_NextPart_000_0023_01C4A708.E0CFFAC0 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

 

           = ;           

       The = Wayland Collegium Faculty Interdisciplinary = Seminar

             Series on Decision Making & = Rationality

 

 

           = ;            Pedro Dal = Bo

 

     = ;            =    Brown University

 

           = ;        Department of = Economics

 

 

           = ;   Tuesday, October 12, 2004 at 4 pm

 

      =        Lubrano Conference Room (CIT 4th floor)

 

           = ; Refreshments will be served at 3:45 pm

 

 

Cooperation Under the Shadow = of the Future: Experimental Evidence from Infinitely Repeated = Games

 

The tension between private incentives that encourage = opportunistic

behavior and the common good that comes from cooperation is a = central

feature of human interaction. The main contribution of game = theory to

the study of this tension and its remedies is to recognize = that

repeated interaction may enable punishment and reward schemes = that

prevent or limit opportunistic behavior and support cooperation. = When

there is always a future, as in infinitely repeated games, = the

credible threat of future retaliation casts ``the shadow of = the

future'' in every decision and can overcome opportunistic = behavior and

support cooperation, thereby solving the tension between = private

incentives and the common good.

 

However, the experimental evidence on infinitely repeated games = is

scarce and in most cases inconclusive or presents = methodological

problems. In this talk I report on a series of experiments = that

overcome some of the shortcomings of previous experiments = on

infinitely repeated games. I find that the possibility of = future

interaction modifies players' behavior resulting in = fewer

opportunistic actions and supporting cooperation, closely = following

theoretical predictions.

 

 

           = ;     Host: Professor Amy = Greenwald

 

 

------=_NextPart_000_0023_01C4A708.E0CFFAC0-- From talks@list.cs.brown.edu Thu Sep 30 21:16:59 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 30 Sep 2004 16:16:59 -0400 Subject: [Brown CS Talks] Brown CS Colloquium: Emery Berger in Lubrano on 10/14/04 at 4 pm Message-ID: <20040930201659.3EE0D44C003@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_0027_01C4A708.E994B330 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Emery Berger Department of Computer Sciences University of Massachusetts Thursday, October 14, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Memory Management for High-Performance Applications Fast and effective memory management is crucial for many applications, including web servers, database managers, and scientific codes. However, current memory managers do not provide adequate support for these applications on modern architectures, severely limiting their performance, scalability, and robustness. In this talk, I describe how to design memory managers that support high-performance applications. First, I show how our Heap Layers infrastructure addresses the software engineering challenges of building efficient memory managers. Next, I'll show why current general-purpose memory managers do not scale on multiprocessors, cause false sharing of heap objects, and systematically leak memory. I describe Hoard, a fast, provably scalable general-purpose memory manager that solves these problems. As an example of its effectiveness, British Telecom uses Hoard to improve real application performance fivefold. Finally, I show how to support server applications that must deal with runaway modules, terminated connections or aborted transactions. I present a generalization of regions and heaps called "reaps" that supports these applications with higher performance and lower memory consumption than current approaches. Host: Professor Shriram Krishnamurthi ------=_NextPart_000_0027_01C4A708.E994B330 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

 

           = ;          BROWN = UNIVERSITY

 

=

    &nbs= p;            COMPUTER SCIENCE COLLOQUIUM

 

 

           = ;            Emery = Berger

 

     = ;          Department of Computer Sciences

 

     = ;            University of Massachusetts

 

 

           = ;   Thursday, October 14, 2004 at 4 pm

 

      =        Lubrano Conference Room (CIT 4th floor)

 

           = ; Refreshments will be served at 3:45 pm

 

 

       Memory Management for High-Performance = Applications

 

Fast and effective memory management is crucial for many = applications,

including web servers, database managers, and = scientific

codes. However, current memory managers do not provide = adequate

support for these applications on modern architectures, = severely

limiting their performance, scalability, and = robustness.

 

In this talk, I describe how to design memory managers that = support

high-performance applications. First, I show how our Heap = Layers

infrastructure addresses the software engineering challenges = of

building efficient memory managers. Next, I'll show why = current

general-purpose memory managers do not scale on multiprocessors, = cause

false sharing of heap objects, and systematically leak memory. = I

describe Hoard, a fast, provably scalable general-purpose = memory

manager that solves these problems. As an example of = its

effectiveness, British Telecom uses Hoard to improve real = application

performance fivefold. Finally, I show how to support = server

applications that must deal with runaway modules, = terminated

connections or aborted transactions. I present a generalization = of

regions and heaps called "reaps" that supports these applications with

higher performance and lower memory consumption than = current

approaches.

 

 

           = ; Host: Professor Shriram = Krishnamurthi

 

 

 

 

------=_NextPart_000_0027_01C4A708.E994B330-- From talks@list.cs.brown.edu Fri Oct 1 20:11:42 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Fri, 1 Oct 2004 15:11:42 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Scott E. Anderson in Barus & Holley, Room 168 on 10/5/04 at 8 pm Message-ID: <20041001191142.8D46E44C086@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_006C_01C4A7C8.F56D3810 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit Seminar BROWN UNIVERSITY Computer Science Department Scott E. Anderson SEA Image Productions Tuesday, October 5, 2004 at 8 pm Barus & Holley, Room 168 The World of Tomorrow - Today: Visual Effects and the Growth of Digital Imaging in Cinema Surveying the digital technologies used on a modern film, both the obvious and the invisible, this talk will cover examples from the current release ``Sky Captain and the World of Tomorrow'' and a short film ``Cinema/Verite.'' These ``smaller'' projects are discussed in in the history and context of Mr. Anderson's past works including: BABE, STARSHIP TROOPERS, HOLLOW MAN, THE ABYSS and TERMINATOR 2. Host: Professor Andy van Dam ------=_NextPart_000_006C_01C4A7C8.F56D3810 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

           = ;             =

           = ;            =     Seminar

           = ;         

           = ;            BROWN = UNIVERSITY

           = ;      Computer Science Department

           = ;             =

           = ;            =

           = ;         

           = ;           = Scott E. = Anderson

 

     = ;          SEA Image = Productions

 

 

           = ;    Tuesday, October 5, 2004 at 8 pm

 

           = ;        Barus & Holley, Room = 168

 

 

The World of Tomorrow - = Today: Visual Effects and the Growth of Digital Imaging in = Cinema

 

Surveying the digital technologies used on a modern film, both = the

obvious and the invisible, this talk will cover examples from = the

current release ``Sky Captain and the World of Tomorrow'' and a = short

film ``Cinema/Verite.''  These ``smaller'' projects are = discussed in in

the history and context of Mr.  Anderson's past works = including: BABE,

STARSHIP TROOPERS, HOLLOW MAN, THE ABYSS and TERMINATOR = 2.

 

 

           = ;     Host: Professor = Andy van Dam

 

 

------=_NextPart_000_006C_01C4A7C8.F56D3810-- From talks@list.cs.brown.edu Tue Oct 5 20:49:12 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 5 Oct 2004 15:49:12 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Dragomir R. Radev in Room 368 on 10/8/04 at 2 pm Message-ID: <20041005194912.D057244C003@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_00A3_01C4AAF2.DC59D9A0 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit Seminar BROWN UNIVERSITY Computer Science Department Dragomir R. Radev University of Michigan Friday, October 8, 2004 at 2 pm Room 368 (CIT 3rd floor) Social network analysis of text Textual data is everywhere, in email and scientific papers, in online newspapers and e-commerce sites. The Web contains more than 200 terabytes of text not even counting the contents of dynamic textual databases. This enormous source of knowledge is seriously underexploited. Textual documents on the Web are very hard to model computationally: they are unstructured, time-dependent, collectively authored, and of uneven importance. Traditional grammar-based techniques don't scale up to address such problems. Novel representations and analytical tools are needed. NewsInEssence (www.newsinessence.com) is a system that crawls the Web for news, automatically clusters it by topic, and produces user-defined extractive summaries of each cluster. A recent addition to the battery of summarization algorithms available to NewsInEssence is the Cosine Centrality method. In this talk I will describe how one can apply the theory of social networks and stochastic processes (in particular rank-based prestige and random walks on undirected graphs) to multi-document text summarization. I will begin my talk with a short tutorial on the mathematics needed for the rest of the talk. If time permits, at the end of the talk, I will quickly describe two recent ongoing projects in my research group: one on machine learning for object classification using random walks on bipartite (feature-object) graphs and another on using phylogenetic techniques for fact tracking in evolving multi-document summarization. Joint work with Gunes Erkan Host: Professor Eugene Charniak ------=_NextPart_000_00A3_01C4AAF2.DC59D9A0 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

           = ;             =

           = ;            =     Seminar

           = ;         

           = ;           BROWN = UNIVERSITY

           = ;      Computer Science Department

 

           = ;             =

           = ;         Dragomir R. Radev

 

  &nb= sp;           &nbs= p; University of Michigan

 

 

           = ;    Friday, October 8, 2004 at 2 pm

 

           = ;        Room 368 (CIT 3rd = floor)

 

 

 

           = ;  Social network analysis of text

 

 

Textual data is everywhere, in email and scientific papers, in = online

newspapers and e-commerce sites. The Web contains more than = 200

terabytes of text not even counting the contents of dynamic = textual

databases. This enormous source of knowledge is = seriously

underexploited. Textual documents on the Web are very hard to = model

computationally: they are unstructured, time-dependent, = collectively

authored, and of uneven importance.  Traditional = grammar-based

techniques don't scale up to address such problems. = Novel

representations and analytical tools are = needed.

 

NewsInEssence (www.newsinessence.com) is a system that crawls = the Web

for news, automatically clusters it by topic, and = produces

user-defined extractive summaries of each cluster. A recent = addition

to the battery of summarization algorithms available to = NewsInEssence

is the Cosine Centrality method.  In this talk I will = describe how one

can apply the theory of social networks and stochastic processes = (in

particular rank-based prestige and random walks on undirected = graphs)

to multi-document text summarization.

 

I will begin my talk with a short tutorial on the mathematics = needed

for the rest of the talk.

 

If time permits, at the end of the talk, I will quickly describe = two

recent ongoing projects in my research group: one on machine = learning

for object classification using random walks on = bipartite

(feature-object) graphs and another on using phylogenetic = techniques

for fact tracking in evolving multi-document = summarization.

 

Joint work with Gunes Erkan

           = ;            =

           = ;            =

           = ;    Host: Professor = Eugene Charniak

 

------=_NextPart_000_00A3_01C4AAF2.DC59D9A0-- From talks@list.cs.brown.edu Tue Oct 12 14:14:39 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Tue, 12 Oct 2004 09:14:39 -0400 Subject: [Brown CS Talks] Brown CS Colloquium: Michael Mitzenmacher in Lubrano on 11/11/04 at 4 pm Message-ID: <20041012131439.04824148005@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_004B_01C4B03B.E699E1A0 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Michael Mitzenmacher Harvard University Thursday, November 11, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Geometrical and Multi-dimensional Generalizations of the Power of Two Choices In this talk I present some new load-balancing results under the paradigm of the ``Power of Two Choices''. In standard analyses, such as for hash-tables, load-balancing is modeled as a balls-and-bins problem: items (balls) are thrown into locations (bins) uniformly at random. The power of two choices paradigm allows each ball two (or more) choices of bins, each taken uniformly at random, which is known to greatly improve the balance of the load. In peer-to-peer and sensor networks, bins may correspond to spaces defined by the underlying geometry that may not be equal in size; locations therefore cannot be modelled as being chosen uniformly at random. We therefore consider geometrical generalizations of the power of two choices. For search engines, we are concerned with word frequencies; the goal is to keep the number of documents with a given word stored at each server balanced simultaneously for all (sufficiently frequent) words. In this case, balls correspond to documents, but now a ball is really a vector (or word list) instead of a single item. We therefore consider multi-dimensional generalizations of the power of two choices. Host: Professor Eli Upfal ------=_NextPart_000_004B_01C4B03B.E699E1A0 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

 

 

           = ;          BROWN = UNIVERSITY

 

=

    &nbs= p;            COMPUTER SCIENCE COLLOQUIUM

 

 

           = ;        Michael Mitzenmacher

 

     = ;             Harvard University

 

 

           = ;  Thursday, November 11, 2004 at 4 pm

 

      =        Lubrano Conference Room (CIT 4th floor)

 

           = ; Refreshments will be served at 3:45 pm

 

 

Geometrical and = Multi-dimensional Generalizations of the Power of

Two = Choices

 

In this talk I present some new load-balancing results under = the

paradigm of the ``Power of Two Choices''.  In standard = analyses, such

as for hash-tables, load-balancing is modeled as a = balls-and-bins

problem: items (balls) are thrown into locations (bins) = uniformly at

random.  The power of two choices paradigm allows each ball = two (or

more) choices of bins, each taken uniformly at random, which is = known

to greatly improve the balance of the load.  In = peer-to-peer and

sensor networks, bins may correspond to spaces defined by = the

underlying geometry that may not be equal in size; locations = therefore

cannot be modelled as being chosen uniformly at random.  We therefore

consider geometrical generalizations of the power of two = choices.  For

search engines, we are concerned with word frequencies; the goal = is to

keep the number of documents with a given word stored at each = server

balanced simultaneously for all (sufficiently frequent) = words.  In

this case, balls correspond to documents, but now a ball is = really a

vector (or word list) instead of a single item.  We = therefore consider

multi-dimensional generalizations of the power of two = choices.

 

 

 

           = ;       Host: Professor Eli = Upfal

 

 

 

 

 

------=_NextPart_000_004B_01C4B03B.E699E1A0-- From talks@list.cs.brown.edu Wed Oct 13 17:27:09 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 13 Oct 2004 12:27:09 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Matt Welsh in Lubrano on 10/27/04 at 3 pm Message-ID: <20041013162709.7C7FB148005@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department Matt Welsh Harvard University Wednesday, October 27, 2004 at 3 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 2:45 pm Market-Based Programming Paradigms for Sensor Networks Sensor networks present a novel programming challenge: that of achieving robust global behavior despite limited resources, varying node locations and capabilities, and changing network conditions. Current programming models typically require that global behavior be specified in terms of the low-level actions of individual nodes. This approach makes it extremely difficult to tune the operation of the sensor network as a whole. Ideally, sensor nodes should self-schedule to determine the set of operations that maximizes that node's contribution to the network-wide task. In this talk, we present market-based macroprogramming (MBM), a new approach for achieving efficient resource allocation in sensor networks. Rather than programming individual sensor nodes, MBM defines a virtual market in which nodes sell goods (such as sensor readings or data aggregates) in response to prices that are established by the programmer. Nodes take actions to maximize their profit, subject to energy budget constraints. The behavior of the network is determined by adjusting the price vectors for each good, rather than by directly specifying local node programs. Nodes individually specialize their operation in response to feedback from payments. Market-based macroprogramming provides a useful set of primitives for controlling the aggregate behavior of sensor networks despite variance of individual nodes. We present the MBM paradigm and a sensor network vehicle tracking application based on this design, as well as a number of experiments demonstrating that MBM allows nodes to operate efficiently under limited energy budgets, while adapting to changing network conditions. This project is in collaboration with Geoff Mainland and David Parkes. Host: Professor Ugur Cetintemel From talks@list.cs.brown.edu Wed Oct 13 17:34:41 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 13 Oct 2004 12:34:41 -0400 Subject: [Brown CS Talks] Brown CS Seminar: George Kollios in Lubrano on 11/3/04 at 3 pm Message-ID: <20041013163441.21B3B148005@null.cs.brown.edu> Seminar BROWN UNIVERSITY Computer Science Department George Kollios Boston University Wednesday, November 3, 2004 at 3 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 2:45 pm Approximate Aggregation Techniques for Sensor Databases In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of database techniques, exemplified by TinyDB and Cougar, which allow users to perform aggregation queries such as MIN, COUNT and AVG on a sensor network. Robust strategies for handling aggregation queries must address the issues of packet loss, node failures and power constraints that are inherent in these systems. With this in mind, we investigate the use of approximate, in-network aggregation techniques using small, duplicate-insensitive sketches. In-network aggregation and the use of sketches keeps power consumed by message transmission in check, while duplicate-insensitivity enables fault-tolerant dispersity routing of sketched aggregates. The talk will place equal weight on theoretical foundations and experimental evaluation. Joint work with Jeffrey Considine, John Byers, and Feifei Li. Host: Professor Ugur Cetintemel From talks@list.cs.brown.edu Thu Oct 14 16:09:26 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 14 Oct 2004 11:09:26 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Bill Strachan in Lubrano on 10/18/04 at 5 pm Message-ID: <20041014150926.B4E7B14800A@null.cs.brown.edu> IBM Info Session, sponsored by IPP BROWN UNIVERSITY Computer Science Department Bill Strachan Watson/IBM Monday, October 18, 2004 at 5 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 4:45 pm IBM Research: A Culture of Innovation William Strachan, Technical Recruiting Program Director for IBM Research, US, will give an overview of IBM Research and discuss internships and & employment opportunities within the Research Division. IBM has the world's largest IT research organization, with about 3,000 scientists and engineers working at eight labs in six countries. IBM Research touches every aspect of IBM's core businesses and beyond. Host: Professor Michael Black From talks@list.cs.brown.edu Wed Oct 20 20:59:08 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 20 Oct 2004 15:59:08 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Hugh Herr in Lubrano on 11/5/04 at 3 pm Message-ID: <20041020195908.57935148005@null.cs.brown.edu> Neurotechnology Seminar BROWN UNIVERSITY Computer Science Department and The Brain Science Program Hugh Herr MIT Media Laboratory and MIT-Harvard Division of Health Sciences and Technology Friday, Nov 5, 2004 at 3 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 2:45 pm New Horizons for Orthotic & Prosthetic Technology: Merging Body and Machine The rehabilitation community is at the threshold of a new age in which orthotic and prosthetic devices will no longer be separate, lifeless mechanisms, but intimate extensions of the human body-- structurally, neurologically, and dynamically. This talk discusses scientific and technological advances that promise to accelerate the merging of body and machine, including the development of actuator technologies that behave like muscle and control methodologies that exploit principles of biological movement. The lecture presents two computer-controlled devices for leg rehabilitation: 1) an external knee prosthesis for trans-femoral amputees and 2) a force-controllable ankle-foot orthosis for stroke, cerebral palsy, or multiple sclerosis patients. For each device, biologically-inspired control schemes automatically modulate device impedance to satisfy patient-specific gait requirements. The lecture outlines the clinical benefits of each assistive device, including improvements in walking economy, biological realism and gait symmetry. Host: Professor Michael Black From talks@list.cs.brown.edu Wed Oct 20 21:28:25 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 20 Oct 2004 16:28:25 -0400 Subject: [Brown CS Talks] Brown CS Seminar: Amy Greenwald in Lubrano on 10/26/04 at 4 pm Message-ID: <20041020202824.E9759148005@null.cs.brown.edu> The Wayland Collegium Faculty Interdisciplinary Seminar Series on Decision Making & Rationality Amy Greenwald BROWN UNIVERSITY Department of Computer Science Tuesday, October 26, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Game-Theoretic Learning: Regret Minimization vs. Utility Maximization No-regret learning algorithms have attracted a great deal of attention in the game-theoretic and machine-learning communities. Whereas rational agents act so as to maximize their expected utilities, no-regret learners are boundedly rational agents that act so as to minimize their ``regret''. In this talk, we analyze the behavior of no-regret learning algorithms in repeated games. Specifically, we introduce a general class of algorithms called no-$\Phi$-regret learning, which includes common variants of no-regret learning such as no-external-regret and no-internal-regret learning. Analogously, we introduce class of game-theoretic equilibria called $\Phi$-equilibria. We show that no-$\Phi$-regret learning algorithms converge to $\Phi$-equilibria. In particular, no-external-regret learning converges to minimax equilibrium in zero-sum games; and no-internal-regret learning converges to correlated equilibrium in general-sum games. Although our class of no-regret learning algorithms is quite extensive, no algorithm in this class converges to Nash equilibrium. From talks@list.cs.brown.edu Fri Oct 22 19:08:18 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Fri, 22 Oct 2004 14:08:18 -0400 Subject: [Brown CS Talks] Brown CS Thesis Defense: Ioannis Tsochantaridis in Lubrano on 10/26/04 at 2-m Message-ID: <20041022180818.F065A14800B@null.cs.brown.edu> BROWN UNIVERSITY Computer Science Department Ioannis Tsochantaridis Thesis Defense Tuesday, October 26, 2004 at 2 pm Lubrano Conference Room (CIT 4th floor) Support Vector Machine Learning for Interdependent and Structure Output Spaces Learning general functional dependencies over arbitrary input and output spaces is one of the key challenges in computational intelligence. Recent progress in machine learning has mainly focused on designing flexible and powerful input representations, for instance via kernel functions. This has greatly increased the range of applicability of learning methods to input representations based on strings, graphs, automata, etc. This talk deals with the complementary issue of generalizing large margin methods, in particular multiclass Support Vector Machines, to prediction problems involving more complex output spaces. We present a novel framework for learning discriminant functions over joint input-output spaces, and present a generic optimization algorithm that exploits the provable sparseness of the solution. Application domains of particular interest for this approach are document categorization, natural language processing, computational biology and optical character recognition. Host: Professor Thomas Hofmann From talks@list.cs.brown.edu Wed Oct 27 14:28:58 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 27 Oct 2004 09:28:58 -0400 Subject: [Brown CS Talks] Brown CS Thesis Defense: Yasemin Altun in Lubrano on 10/28/04 at 1 pm Message-ID: <20041027132858.7CB38148005@null.cs.brown.edu> BROWN UNIVERSITY Computer Science Department Yasemin Altun Thesis Defense Thursday, October 28, 2004 at 1 pm Lubrano Conference Room (CIT 4th floor) Discriminative Methods for Label Sequence Learning The discriminative learning framework is one of the very successful fields of machine learning. The methods of this paradigm, such as Boosting, Support Vector Machines and Gaussian Processes, have significantly advanced the state-of-the-art for classification by improving the accuracy and increasing the applicability of machine learning methods. One of the key benefits of these methods is their ability to learn efficiently in high-dimensional feature spaces, either by the use of implicit data representations via kernels or by explicit feature induction. However, traditionally these methods do not exploit dependencies between class labels where more than one label is predicted. Many real-world classification problems involve sequential, temporal or structural dependencies between multiple labels. The goal of this research is to generalize discriminative learning methods for such scenarios. In particular, we focus on label sequence learning. Label sequence learning is the problem of inferring a state sequence from an observation sequence, where the state sequence may encode a labeling, annotation or segmentation of the sequence. Prominent examples include part-of-speech tagging, named entity classification, information extraction, continuous speech recognition, and secondary protein structure prediction. In this thesis, we present three novel discriminative methods that are generalizations of AdaBoost, multiclass Support Vector Machines (SVM) and Gaussian Processes (GP) for label sequence learning. These techniques combine the efficiency of dynamic programming methods with the advantages of the state-of-the-art learning methods. We present theoretical analysis and experimental evaluations of pitch accent prediction, named entity recognition and part-of-speech tagging which demonstrate the advantages over classical approaches like Hidden Markov Models as well as the state-of-the-art methods like Conditional Random Fields. Host: Professor Thomas Hofmann From talks@list.cs.brown.edu Thu Oct 28 18:59:02 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 28 Oct 2004 13:59:02 -0400 Subject: [Brown CS Talks] Brown CS Colloquium: Baruch Schieber in Lubrano on 11/4/04 at 4 pm Message-ID: <20041028175902.3468A14800A@null.cs.brown.edu> BROWN UNIVERSITY COMPUTER SCIENCE COLLOQUIUM Baruch Schieber IBM T. J. Watson Research Center Thursday, November 4, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm Online QoS Buffer Management We study the behavior of algorithms for buffering packets weighted by different levels of Quality of Service (QoS) guarantees in a single queue. Buffer space is limited, and packet loss occurs when the buffer overflows. We describe a modification of the preemptive greedy algorithm of Kesselman et al. (ESA 2003) for buffer management and give an analysis to show that this algorithm achieves a competitive ratio of at most 1.75. This improves upon recent work showing a 1.98 competitive ratio, and previous result that shows the simple greedy algorithm has a competitive ratio of 2. This is joint work with Nikhil Bansal, Lisa Fleischer, Tracy Kimbrel, Mohammad Mahdian and Maxim Sviridenko Host: Professor Philip Klein From talks@list.cs.brown.edu Wed Nov 3 18:39:16 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 3 Nov 2004 13:39:16 -0500 Subject: [Brown CS Talks] Oliver Bimber in Lubrano on 11/8/04 at 4pm In-Reply-To: <20041022180818.F065A14800B@null.cs.brown.edu> Message-ID: <20041103183916.1CEF414800A@null.cs.brown.edu> BROWN UNIVERSITY Computer Science Department Jun. Prof. Dr. Ing. Oliver Bimber Bauhaus University, Weimar, Germany Monday, November 8, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Augmented Holograms and Smart Projectors Optical holograms provide a terapixel resolution and are able to present an information content in the range of terabytes in real-time. Both are dimensions that will not be reached by computer graphics and conventional displays within the next years. In contrast to computer graphics, optical holograms are not interactive. Consequently, holography and computer graphics are being used as tools to solve individual research, engineering, and presentation problems within several domains. Up until today, however, these tools have been applied separately. Our intention is to combine both technologies to create a powerful tool for science, industry and education. We are currently investigating the possibility of integrating computer generated graphics and holograms. Our goal is to combine the advantages of conventional holograms with the advantages of today's computer graphics capabilities. Using video projectors, the reference wave that reconstructs holograms can be digitized. This enables a synchronized integration of interactive graphical elements into optical holograms. Video projectors will play a major role in future home entertainment and edutainment applications. However, we have to give up living space and ambience to set up artificial canvases that have to be as large as the desired image. We are investigating smart projectors that are able to display correct images onto arbitrary existing screen surfaces, like wallpapered walls, natural stone walls or window curtains. Thus they can function without an artificial canvas and consequently leave a bit more freedom to us in the decision on how to arrange our living space. State-of-the-art graphics chips support per-pixel geometric and photometric image correction in real-time, and enable a correct projection onto arbitrary surfaces. Host: Andries van Dam _______________________________________________ The Computer Science Department is located at 115 Waterman St., Providence, RI. Our Calendar of Events at http://www.cs.brown.edu/events lists all of our talks. If you would like to be removed from (or added to) our seminar mailing list, or if you would prefer to receive only announcements pertaining to IPP talks, please send email containing your request to mailto:talks-admin@cs.brown.edu. We'd very much appreciate your forwarding these announcements to colleagues who may also have an interest. Thanks for your cooperation. From talks@list.cs.brown.edu Thu Nov 4 15:51:56 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 4 Nov 2004 10:51:56 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Aldo Rustichini in Lubrano on 11/23/04 at 4 pm Message-ID: <20041104155156.A584214800A@null.cs.brown.edu> The Wayland Collegium Faculty Interdisciplinary Seminar Series on Decision Making & Rationality Aldo Rustichini Department of Economics University of Minnesota Tuesday, November 23, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 3:45 pm An Economist's Point of View on Neuroeconomics In the talk I will present several recent results in the growing area of Neuroeconomics. The topics will include the role of learning and planning, the role of emotions in decisions, the importance of the personality characteristics in strategic behavior. In each case an effort will be made to test whether traditional concepts of game theory as well as, more generally, economic theory are useful in the enterprise of determining the neural foundation of human behavior. Host: Professor Amy Greenwald From talks@list.cs.brown.edu Thu Nov 18 14:56:48 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 18 Nov 2004 09:56:48 -0500 Subject: [Brown CS Talks] Brown CS Lecture: Michael O. Rabin in Lubrano on 12/2/04 at 4 pm Message-ID: <20041118145649.001EC14800C@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_0018_01C4CD54.EBCD3E20 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit The Fourth Annual PARIS KANELLAKIS Memorial Lecture BROWN UNIVERSITY Department of Computer Science Michael O. Rabin Harvard University Thursday, December 2, 2004 at 4 pm Lubrano Conference Room (CIT 4th floor) Hyper-Encryption via Virtual Satellite Modern encryption methods are based for their security on unproven assumptions such as the computational intractability of factorization of large integers. This has prompted research into alternatives such as quantum cryptography. We consider an encryption method employing an intensive public stream of random bits. The sender and receiver use a shared private key to extract from the stream one-time pads used to encrypt messages. I have shown, together with Y. Aumann and Y.Z. Ding, that this leads to provably unbreakable encryption and to everlasting secrecy. More recently we created the Virtual Satellite model, now being implemented at Harvard, which again provides provably unbreakable encryption. The talk will be self contained. Michael Rabin is T.J. Watson Sr. Professor of CS at Harvard University. He received his Ph.D. from Princeton University, where he had his first academic appointment. He was Albert Einstein Professor of Mathematics at the Hebrew University, serving as its Academic Head from 1972 to 1975. His awards include the ACM Turing Award, The IEEE Charles Babbage Award, The Harvey Prize for Science and Technology, and the Israel Prize in Computer Science, and the ACM Kanellakis Prize for theory and Practice. He has been elected to five major academies and holds five honorary degrees. Host: Professor Tom Doeppner A reception will follow in the atrium ------=_NextPart_000_0018_01C4CD54.EBCD3E20 Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

          =             =              =      

 

         The = Fourth Annual PARIS KANELLAKIS Memorial Lecture

 

       =        =           BROWN = UNIVERSITY

 

       =            Department of = Computer Science

 

       =        =           Michael O. = Rabin

 

       =        =          Harvard = University

 

 

       =          Thursday, December 2, 2004 = at 4 pm

 

       =        Lubrano Conference Room (CIT 4th = floor)

 

 

       =        Hyper-Encryption via Virtual = Satellite

 

Modern encryption methods are based for their security on = unproven

assumptions such as the computational intractability of = factorization

of large integers. This has prompted research into = alternatives such

as quantum cryptography. We consider an encryption method = employing an

intensive public stream of random bits. The sender and = receiver use a

shared private key to extract from the stream one-time = pads used to

encrypt messages. I have shown, together with Y. Aumann = and Y.Z. Ding,

that this leads to provably unbreakable encryption and to = everlasting

secrecy. More recently we created the Virtual Satellite = model, now

being implemented at Harvard, which again provides = provably

unbreakable encryption. The talk will be self = contained.

 

Michael Rabin is T.J. Watson Sr. Professor of CS at = Harvard

University. He received his Ph.D. from Princeton = University, where he

had his first academic appointment. He was Albert = Einstein Professor

of Mathematics at the Hebrew University, serving as its = Academic Head

from 1972 to 1975. His awards include the ACM Turing = Award, The IEEE

Charles Babbage Award, The Harvey Prize for Science and = Technology,

and the Israel Prize in Computer Science, and the ACM = Kanellakis Prize

for theory and Practice.  He has been elected to = five major academies

and holds five honorary degrees.

 

 

       =             Host: = Professor Tom Doeppner

 

 

       =        A reception will follow in the = atrium

 

 

 
------=_NextPart_000_0018_01C4CD54.EBCD3E20-- From talks@list.cs.brown.edu Mon Nov 29 16:44:38 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Mon, 29 Nov 2004 11:44:38 -0500 Subject: [Brown CS Talks] Brown CS' (Industrial Partner Program) Adam Leventhal in Lubrano on 11/30/04 at 4 pm Message-ID: <20041129164438.2B1BE14800B@null.cs.brown.edu> Industrial Partners Program (IPP) Seminar BROWN UNIVERSITY Computer Science Department Adam Leventhal '01 Sun Microsystems Tuesday, November 30, 2004 4 pm Lubrano Conference Room (CIT 4th floor) Pizza break at 3:45 pm (followed by an infossession) Solaris Kernal Group Tech Talk Solaris 10 is the most innovating OS release in Sun's history. Adam Leventhal, one of the 8 Brown CS alumni in the Solaris kernel group, will discuss some of the new technologies in Solaris including a new file system, virtualization environment and dynamic tracing framework. Sun also plans to release Solaris under and open source license -- find out what that means for systems research as well as hacking OS code in your dorm room. Host: Professor Tom Doeppner From talks@list.cs.brown.edu Wed Dec 1 19:44:31 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 1 Dec 2004 14:44:31 -0500 Subject: [Brown CS Talks] Brown CS Seminar Series: Rajmohan Rajaraman in Lubrano on 12/8/04 at noon Message-ID: <20041201194431.58E14148005@null.cs.brown.edu> Department of Computer Science Seminar Series BROWN UNIVERSITY Rajmohan Rajaraman Northeastern University Wednesday, December 8, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:15 am Algorithms for Multi-Query Processing in Sensor Networks A powerful database abstraction for sensor networks has recently emerged in which clients program the sensors using a declarative query language, permitting the system to perform low-level optimizations for effective query processing. This talk concerns the energy-efficient processing of multiple aggregate queries in sensor networks. We consider a sensor network in which queries are issued through a special gateway node, sensor data are processed within the network and the results propagated to the gateway. In the first part of the talk, we present an algorithm for computing an aggregation schedule (tree) that simultaneously well-approximates the communication cost for every possible query. In obtaining this result, we have developed a new notion of universal approximation, which has diverse applications and may be of independent interest. In the second part of the talk, we assume a fixed aggregation tree and present new techniques for encoding the results of query computations, aimed at minimizing the communication cost for processing multiple aggregate queries. Host: Professor Ugur Cetintemel From talks@list.cs.brown.edu Wed Dec 1 19:55:23 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Wed, 1 Dec 2004 14:55:23 -0500 Subject: [Brown CS Talks] Brown CS Seminar: Robert Moorhead in Lubrano on 12/9/04 at noon Message-ID: <20041201195523.790A5148005@null.cs.brown.edu> A Department of Computer Science Seminar BROWN UNIVERSITY presents Robert Moorhead Director, Visualization, Analysis, and Imaging Lab GeoResource Institute Mississippi State University Thursday, December 9, 2004 at noon Lubrano Conference Room (CIT 4th floor) Refreshments will be served at 11:45 am "A Tale of Two Centers" The ERC at Mississippi State University originated in 1990 as the NSF Engineering Research Center (ERC) for Computational Field Simulation at MSU, which focused directly on the application of high performance computing (HPC) for computational field simulation of fluid flow, heat and mass transfer, and structural mechanics for applications to aircraft, spacecraft, ships, automobiles, environmental, ocean, and biological flow problems. Initially funded by the NSF Engineering Research Center (ERC) Program in 1990 -- one of three NSF ERCs funded that year out of 48 proposals-this ERC was the only one of the NSF ERCs with its focus directly on high performance computing (HPC). Over the 11-year life cycle that NSF ERCs have, the Center increased its annual funding by an order of magnitude, graduating from the NSF ERC program in 2001 and now continuing as a self-sufficient research center with funding from a range of federal agencies and industry. The ERC now consists of five loosely federated centers focused on high performance computing that have a cumulative annual extramural funding of over $30M. These five centers are: Center for Advanced Vehicular Systems Center for Computational Sciences Center for DoD Programming Environment and Training Computational Simulation and Design Center GeoResources Institute This talk will discuss how the original ERC came into being and how it evolved into the five centers that now exist. Host: Professor David Laidlaw From talks@list.cs.brown.edu Thu Dec 2 14:41:16 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 2 Dec 2004 09:41:16 -0500 Subject: [Brown CS Talks] Yiorgos Makris at Barus & Holley in Studio Lab (Room 194) on 12/3/04 at 3 pm Message-ID: <20041202144116.E454A148005@null.cs.brown.edu> BROWN UNIVERSITY presents Yiorgos Makris Yale University Friday, December 3, 2004 at 3 pm Barus & Holley Studio Lab (Room 194) Parity-Based Concurrent Error Detection in Finite State Machines I will discuss a non-intrusive methodology for Concurrent Error Detection (CED) in Finite State Machines (FSMs). The proposed method is based on compaction and monitoring of the state/output bits of an FSM via parity trees. While transient errors such as Single Event Upsets (SEU) may affect more than one state/output bit, not all combinations of state/output bits constitute potential erroneous cases for a given error model. Therefore, it is possible to compact them without loss of error information. Concurrent error detection can then be performed through hardware that predicts the values of the compacted state/output bits and compares them to the actual values of the FSM. In order to minimize the number of necessary parity functions, we formulate the problem as a set of integer constraints and we employ linear programming and randomized rounding to approximate it. Experimental results indicate that only a small number of parity trees are typically sufficient to preserve the detectability of all errors arising from realistic models. Thus the anticipated hardware overhead is reduced significantly as compared to duplication-based CED. Next, I will focus on the actual hardware overhead of the proposed CED method and I will demonstrate that minimization of the number of parity trees does not necessarily minimize the corresponding hardware cost. I will then present a systematic search approach that exploits the correlation between the hardware cost of a function and its entropy, in order to select parity trees that minimize the actual hardware cost, while achieving lossless compaction. Experimental results demonstrate that this method achieves significant hardware reduction over methods that minimize the number of parity trees. Yiorgos Makris is an Assistant Professor of Electrical Engineering and Computer Science at Yale University. He holds a Diploma of Computer Engineering from the University of Patras in Greece, and an MS and PhD in Computer Engineering from the University of California, San Diego. His research interests are in the areas of test and reliability for digital and analog circuits and systems. From talks@list.cs.brown.edu Thu Dec 9 16:51:32 2004 From: talks@list.cs.brown.edu (talks@list.cs.brown.edu) Date: Thu, 9 Dec 2004 11:51:32 -0500 Subject: [Brown CS Talks] Brown CS Demo: CS137 Virtual Reality Design in the CAVE on 12/14/04 Message-ID: <20041209165132.C117F148005@null.cs.brown.edu> This is a multi-part message in MIME format. ------=_NextPart_000_0009_01C4DDE5.6D950AF0 Content-Type: text/plain; charset="US-ASCII" Content-Transfer-Encoding: 7bit CS137: Virtual Reality Design for Science BROWN UNIVERSITY Interactive Bat Flight Visualizations in VR Tuesday December 14th, 2004, 11am to 1pm. The CAVE at Brown 180 George St. (corner of Brook St.) Come see three great projects created by undergrads from RISD and Computer Science collaborating together. They have created amazing visuals and interaction techniques to help scientists understand how bats fly. Just to give you an idea of their cool creations: they have incorporated a big comfy armchair into their designs, they have taken apart computer mice and created their own cool input devices, they even have virtual sparklers! All of it in the context of a scientific study of bat flight led by scientists at the Ecology and Evolutionary Biology Department. Come all! 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A frequent complication is that data contains multiple structures. Most existing algorithms do not offer any control over which structure is returned and those which do typically require the user to characterize the desired structure in advance. However, a user may not know in advance which solution is desired. We instead introduce a novel approach to the problem: we incorporate knowledge of structure which is not desired. We focus on the task of clustering data which contains multiple interesting groupings of items. In contrast to existing constrained clustering techniques which bias search towards certain clusterings, our goal is to develop techniques which steer search away from known clusterings. As a result, they reveal novel, "orthogonal" clusterings. We formally define the problem and propose three algorithmic approaches based on expectation maximization, information bottleneck, and ensemble clustering. We present derivations of each technique and discuss theoretical results. Experimental results on synthetic, document, and image data validate and illustrate the relative merits of each of the three approaches. We show how to extend these techniques to enumerate multiple clusterings in a data set. Finally we leverage the techniques to improve performance over state-of-the-art methods in semi-supervised classification. Host: Professor Thomas Hofmann