- talks - lists.cs.princeton.edu

11am Tue Mar 31 talk on information assurance research at the NSA
by Jennifer Rexford 18 Mar '09

18 Mar '09

Title: The Information Assurance Mission and Research at National Security Agency (NSA) Speakers: Mr. Richard George, Dr. Robert Runser, and Ms. Christine Coldwell Date/time: 11am Tuesday March 31 Location: 101 Friend Center Mr. Richard George, the Information Assurance Technical Director at NSA, will discuss the information assurance mission at NSA, the historical context for this mission, and the pillars necessary to ensure information security in today's ever-changing world of technology and threats. Dr. Robert Runser *01, a Research Scientist at NSA, will present a brief overview of research at NSA and discuss results from a forward-looking project investigating the potential of fiber-optic quantum key distribution (QKD) as a means to secure future networks. Ms. Christine Coldwell '99 *00, a Senior Technical Development Program Analyst, will describe her career path in industry and government, how a Princeton education has prepared her, and why she is inspired by her career at the National Security Agency. Hosted by Professor Paul Prucnal CNSA Center for Networks Science and Applications

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Talk today - 4:20pm COS 105
by Ginny Hogan 18 Mar '09

18 Mar '09

Moni Naor, Weizmann Institute, talk "Leakage Resistant Public key Cryptography" will be today at 4:20pm -Computer Science Room 105 -

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3pm Thu Mar 26 talk on enterprise networks in CS 402
by Jennifer Rexford 11 Mar '09

11 Mar '09

Professor Aditya Akella is visiting from U. Wisconsin-Madison on Thursday March 26, and giving a talk 3-4pm in room 402 -- see title and abstract below. Please let me know if you would like to meet with Aditya and if you would like to join for lunch/dinner: Speaker: Aditya Akella, U. Wisconsin-Madison Title: Managing the Complexity of Modern Enterprise Networks Place/time: 3-4pm Thu Mar 26 in CS 402 Abstract: Operator interviews and anecdotal evidence suggest that an operator's ability to manage a network decreases as the network becomes more complex. Today, there is no way to quantify how complex a network's design is, nor how complexity may impact network management activities. In this talk, I will present a suite of "complexity models" that describe the routing design and configuration of a network in a succinct fashion, abstracting away details of the underlying configuration languages. Our models, and the complexity metrics arising from them, capture the difficulty of configuring control and data plane behaviors on routers. They also measure the inherent complexity of the reachability constraints that a network implements via its routing design. Our models simplify network design and management by facilitating comparison between alternative designs for a network. We tested our models on seven networks, including four universities and three enterprises. We validated the results through systematic interviews with the operators of five of the networks. We found the metrics to be predictive of the issues operators face when reconfiguring their networks. A surprising result of our study was uncovering the reasons for operators choosing the designs they did. Given the frequency with which configuration errors are responsible for major outages, we believe that creating techniques to quantify the complexity of a network's design is an important first step to reducing that complexity. In databases, software engineering and other fields, metrics and benchmarks have driven the direction of the field by defining what is desirable and what is not. In proposing these metrics, we hope to start a similar conversation for network design. I will end the talk with a brief description of our recent work on WAN optimization.

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Talk Today Computer Science Dept.
by Ginny Hogan 04 Mar '09

04 Mar '09

Bjarne Stroustrup, Texas A&M, will present his talk, "50 Years of C++", at 4:15pm today Computer Science Room 105 -

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today's Talk postponed
by Melissa Lawson 02 Mar '09

02 Mar '09

John Langford's visit and talk for today (March 2) have been POSTPONED due to the snowstorm. Announcement for John Langford's rescheduled talk, as well as for future talks in the speaker series, will be sent to ML- stats-talk, which is a mailing list for announcing talks related to machine learning and statistics at Princeton. The list can be joined by following this link: https://lists.cs.princeton.edu/mailman/listinfo/ml-stat-talks

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Talk by John Langford next Monday, March 2 -- 1st speaker of the Machine Learning Speaker Series
by Melissa Lawson 25 Feb '09

25 Feb '09

This semester, the machine learning group will be organizing a speaker series, with the goal of inviting prominent researchers in machine learning to give talks at our department. The series is being sponsored by Yahoo!. Our first speaker is John Langford from Yahoo! Research, who will be visiting the department next Monday (March 2). John is an expert in the theory of machine learning. He also writes a popular blog about machine learning, http://hunch.net. John will be giving a talk at 4:25pm, in CS 105 (small auditorium). The title and abstract for his talk appear below. Future talk announcements for the speaker series will be sent to ML- stats-talk, which is a mailing list for announcing talks related to machine learning and statistics at Princeton. The list can be joined by following this link: https://lists.cs.princeton.edu/mailman/listinfo/ml-stat-talks If you'd like to meet John on Monday, details about his schedule will be sent to ML-stats-talk soon. Title: Use of Hash in Machine Learning Abstract: I'll describe a learning algorithm (Vowpal Wabbit) which effectively learns on and uses terascale datasets with a collection of tricks. One of the central tricks is rather fascinating---it uses a core hash representation which is both extremely time and space efficient. Stated another way, we use a sparsity preserving random projection, for which we prove convergence bounds reminiscent of the JL Lemma or locality sensitive hashing. This trick enables otherwise impossible applications like building a personalized spam filter for hundreds of thousands of users that easily fits into the RAM of a single machine.

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A Golovinskiy preFPO
by Melissa Lawson 24 Feb '09

24 Feb '09

Alex Golovinskiy will present his preFPO on Wednesday March 4 at 11:30 AM in Room 401 (note room). The members of his committee are: Tom Funkhouser, advisor; Adam Finkelstein and Szymon Rusinkiewicz, readers; David Dobkin and Rob Schapire, nonreaders. Everyone is invited to attend his talk. His abstract follows below. ------------------------ Algorithms for analyzing the texture, symmetry, and part structure of 3D surface models Abstract: While much of computer graphics research has focused on low-level primitives, many computer graphics applications require reasoning about higher level structures. In response to this need, research has emerged to find and take advantage of higher level structures such as textural properties of geometry, symmetries, and functional parts. We advance this line of research in several directions. First, we present a method for analyzing and modifying detailed facial geometry. We introduce a statistical technique for the analysis and synthesis of small three-dimensional facial features, such as wrinkles and pores. As an initial step, our method separates the skin surface details from a smooth base mesh. Then, we analyze the resulting displacement maps and synthesize new geometry using tools from texture synthesis research. We demonstrate this method for analysis of changes of facial texture with respect to age and gender, detail-preserving interpolation between high-resolution face models, adding detail to low-resolution face models, and adjusting the apparent age of face models. Second, we present a framework for symmetry-aware mesh processing. Although perfect, partial, and approximate symmetries are pervasive in real-world geometry, current geometry processing algorithms ignore them. We present a framework in which, given a set of symmetries, we (i) warp the geometry to be symmetric, and (ii) re-mesh a model to have symmetric triangulation. We show how to use this framework to create algorithms that respect the symmetries of a model, and demonstrate applications for modeling, beautification, and simplification of nearly symmetric surfaces. Third, we present several investigations into segmenting meshes into parts. We present a hierarchical aggregation algorithm for mesh segmentation. We then expand this algorithm to consistently segment a set of meshes. We also show how to modify mesh segmentation algorithms to produce a soft, randomized version of segmentation. Finally, we present a framework for finding and recognizing objects in outdoor point cloud scans. We present methods for locating potential objects, segmenting them, and classifying them. We quantitatively evaluate these models on a part of an Ottawa scan.

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FW: CS Events Calendar
by Ginny Hogan 18 Feb '09

18 Feb '09

_____ From: Laura Cummings-Abdo [mailto:lcumming@Princeton.EDU] Sent: Wednesday, February 18, 2009 10:34 AM To: Ginny Hogan Subject: CS Events Calendar Hi Ginny, Could you put this on the CS Events Calendar? Thanks. Symposium: Community and Municipal Wireless Systems Title: Community and Municipal Wireless Systems When: Thursday, March 5, 2009 - 4:30 PM - 6:30 PM Where: Woodrow Wilson School, Robertson Hall, Bowl 1 The Center is committed to bringing together technologists and policy scholars around critical issues in the regulation of technology and the use of technology to achieve policy ends. We have identified the complex set of issues around community and municipal wireless as an especially important topic, due to its potential to address issues of equity in access to the Internet and related technologies, as well as its potential to increase the effectiveness of municipal services. At the same time, we recognize that wireless projects have met with mixed success, and that both technical and political/economic issues remain to be resolved. We hope that this symposium will clarify the state of play, point to challenges and unanswered questions, and perhaps inspire some students and younger scholars to take a long-term interest in this area. Panelists: H. Vincent Poor, Dean of Princeton University's Engineering School Sharon Gillett, Commissioner of the State of Massachusetts Department of Telecommunications and Cable Greg Goldman, Chief Executive Officer, Wireless Philadelphia Sascha Meinrath, Research Director, New America Foundation Wireless Futures Program and Coordinator, Open Source Wireless Coalition http://citp.princeton.edu/events/community-wireless-panel/ Laura Cummings-Abdo Program Assistant Center for Information Technology Policy Princeton University Sherrerd Hall, Room 303 Princeton, NJ 08544 Tel: 609-258-9658 Fax: 609-964-1855 <http://citp.princeton.edu/> http://citp.princeton.edu/ Sherrerd-HallSmall

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E Banks FPO
by Melissa Lawson 17 Feb '09

17 Feb '09

Eric Banks will present his FPO on Monday February 23 at 1:30PM in Room 402. The members of his committee are: Mona Singh, advisor; Olga Troyanskaya and Bernard Chazelle, readers; Tom Funkhouser and David Blei, nonreaders. A copy of his thesis, "Algorithms for Analyzing and Interrogating Protein Interaction Networks", is on display in room 310. Everyone is invited to attend his talk.

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U Syed preFPO
by Melissa Lawson 13 Feb '09

13 Feb '09

Umar Syed will present his preFPO on Friday February 20 at 10:30AM in Room 302. The members of his committee are: Rob Schapire advisor; David Blei and Warren Powell (ORF), readers; Michael Littman (Rutgers) and Yael Niv (PSY), non-readers. Everyone is invited to attend his talk. His abstract follows below. --------------------------- Title: Algorithms for Hybrid Supervised/Reinforcement Learning Problems Abstract: Reinforcement and supervised learning are two different approaches to machine learning. For an illustration their differences, consider the task of learning to drive a car. A reinforcement learning algorithm learns how to drive be trying several different driving behaviors, and uses feedback from the environment to decided which behavior is best. The feedback is delivered in the form of rewards, which reflect the desirability of various events such as crashing, staying on the road, etc. By contrast, a supervised learning algorithm passively observes an expert driver, and attempts to imitate his driving behavior. In general, reinforcement learning algorithms are concerned with maximizing reward, and supervised learning algorithms are concerned with matching observed behavior. In this talk, I will discuss learning algorithms that combine aspects of both reinforcement and supervised learning, leveraging the strengths of each approach. Specifically, I will describe algorithms for (i) using observations from an expert to learn high-reward behavior in environments where the true rewards are only partially known; (ii) improving the imitation of an expert's behavior by imposing reward-based constraints on the space of possible behaviors; (iii) learning high-reward behavior in an environment where the rewards can abruptly, but predictably, change. I will present theoretical performance guarantees for each of our algorithms, which in some cases represent substantial improvements over guarantees for earlier methods. Our algorithms are motivated by problems in vehicle navigation, spoken dialog systems, and web search. I will present experimental results from some of these domains. Includes joint work with Rob Schapire, Michael Bowling (U Alberta), Jason Williams (AT&T), Nina Mishra (Microsoft), and Alex Slivkins (Microsoft).

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