SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for March
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Defending Networked Resources Against Unwelcome Request Floods
Mon, Mar 05, 2007 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Michael WalfishMassachusetts Institute of TechnologyAbstract: The Internet is afflicted by unwelcome "requests", defined broadly as claims on a scarce resource, such as a server's CPU(in the case of spurious traffic whose purpose is to deny service) or a human's attention (in the case of spam). Traditional responses to these problems apply heuristics: they try to identify "bad" requests based on their content (e.g., in the way that spam filters analyze an email's text). This talk argues that heuristic attempts at filtering are inherently
gameable and instead presents two systems that limit request volumes directly. The first is a denial-of-service mitigation in which clients are encouraged to automatically send *more* traffic to a besieged server. The "good" clients can thereby compete equally with the "bad" ones. The second is a system for enforcing *per-sender email quotas* to control spam. This system scales to a workload of millions of requests per second, tolerates Byzantine faults in its constituent hosts, and resists a variety of external attacks. Biography: Michael Walfish is a Ph.D. student in computer science at M.I.T. He received his B.A. from Harvard in 1998 and then worked for four years, three of those at Digital Fountain, Inc. His research interests are in networked systems, with sub-interests in security, performance, and network architecture.Host: Ramesh GovindanSnack served!
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Nancy Levien
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Statistical Failure Diagnosis in Software and Systems
Tue, Mar 06, 2007 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Alice ZhengCarnegie Mellon UniversityAbstract:As software and systems become increasingly complex, the task of debugging also becomes increasingly difficult. Manual diagnosis can require sifting through millions of lines of code and output logs. In addition, large systems contain many components, each complex on its own, and often interacting in unexpected ways.I present a case study illustrating how statistical machine learning algorithms, along with appropriate system instrumentation, can aid in failure
diagnosis. I propose a statistical software debugging framework that collects information from past successes and failures via fine-grained instrumentation of the program and then analyzes this information to locate suspicious
program predicates. I discuss the algorithmic challenges of the approach, and demonstrate a bi-clustering algorithm that is effective at simultaneously clustering failed runs and selecting useful predicates. Using this approach,
it took a programmer 20 minutes to find a long-standing bug in a real-world software program which he had never seen before.This work is done in collaboration with Ben Liblit (U. Wisconsin, Madison), Michael Jordan (U.C. Berkeley), Alex Aiken and Mayur Naik (Stanford).Biography:Alice Zheng received her Ph.D. from UC Berkeley in 2005 and is currently a postdoctoral fellow at Carnegie Mellon University. Her interests lie in
applied machine learning, in particular to computer systems, software, and networks. Current projects include statistical software debugging,
performance diagnosis of distributed file systems, efficient internet traffic measurements, and modeling social networks.Hosted by Stefan SchaalRefreshments will be served.
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Nancy Levien
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CS Colloquium Series - Michael Goodrich
Tue, Mar 20, 2007 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Blood on the Computer: How Algorithms for Testing Blood Samples can be used for DNA Sequencing, Wireless Broadcasting, and Network SecurityDr. Michael GoodrichUniversity of California-IrvineAbstract:
This talk discusses combinatorial group testing, which began from work on detecting diseases in blood samples taken from GIs in WWII. Given a parameter d, which provides an upper bound on the number of defective (e.g., diseased) samples, the main objective of such problems is to design algorithms that identify all the defective samples without explicitly testing all n samples. This classic problem has a number of interesting modern applications, and we provide several new efficient algorithms that can be applied in these new contexts. In particular, modern applications we will discuss include problems in DNA sequencing, wireless broadcasting, and network security.Biography:
Prof. Goodrich received his B.A. in Mathematics and Computer Science from Calvin College in 1983 and his PhD in Computer Sciences from Purdue University in 1987. He served as a professor of computer science at Johns Hopkins University from 1987-2001, and a professor of computer science since 2001 at UC-Irvine, where he also serves as director of the Center of Cyber-Security and Privacy, as well as Equity Advisor and Associate Dean for Academic Personnel in the Donald Bren School of Information and Computer Sciences. He has also served on the faculties of Univ. of Illinois and Brown University during sabbatical visits.
Dr. Goodrich's research is directed at the design of high performance algorithms and data structures for solving large-scale problems motivated from information assurance and security, the Internet, information visualization, and geometric computing. He has pioneered and led research on efficient parallel and distributed solutions to a number of fundamental problems, including sorting, convex hull construction, segment intersection reporting, fixed-dimensional linear programming, polygon triangulation, Voronoi diagram construction, and data authentication.
With nearly 200 publications, including several widely adopted books, his recent work includes contributions to efficient and secure distributed data structures, authenticated geometric searching, IP traceback, and network/grid security. He is an ACM Distinguished Scientist, a Compere Loveless Fellow, and a member of the Fulbright Senior Specialist Roster, the Sigma Xi Scientific Research Honor Society, and the editorial boards of several top journals on algorithms. He is a recipient of the IEEE Computer Society Technical Achievement Award, the NSF Research Initiation Award, the DARPA Spirit of Technology Transfer Award, the Brown Univ. Award for Technological Innovation, the ACM Recognition of Service Award, and the Pond Award for Excellence in Undergraduate Teaching.
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Nancy Levien
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CS Distinguished Lecture Series
Thu, Mar 22, 2007 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Prof. Martha Pollack
University of MichiganTitle: Intelligent Assistive Technology: The Present and the FutureAbstract: Recent advances in two areas of computer sciencewireless sensor networks and AI inference strategies have made it possible to envision a wide range of technologies that can improve the lives of people with people with physical, cognitive, and/or psycho-social impairments. Indeed, some of these same "assistive technologies" can also be a boon for people without impairments. This talk will survey current projects aimed at the development of intelligent assistive technology and will speculate about future design challenges and opportunities.Biography: Martha E. Pollack is a Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, where she also chairs the Computer Science and Engineering Division. A Fellow of the American Association for Artificial Intelligence, Pollack has conducted research in the areas of automated planning and execution monitoring, temporal reasoning and constraint satisfaction, and natural language processing, as well as on assistive technology for cognitively impaired people. In April of 2004 she testified before the U.S. Senate Special Committee on Aging about the potential value of assistive technology in an aging world.Hosted by: Prof. Maja MataricLocation: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Nancy Levien
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Efficient and Private Distance Approximation
Mon, Mar 26, 2007 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
David WoodruffMassachusetts Institute of TechnologyAbstract:I will cover two of my results in distance approximation. Consider the setting in which two parties want to approximate the distance between their input vectors.First I will consider l_2, the Euclidean distance. It is known how to approximate l_2 efficiently. However, if we require the protocol to be private, that is, neither party can learn more than what follows from the distance and his/her private input, much less is known. Feigenbaum, Ishai, Malkin, Nissim, Strauss, and Wright [FIMNSW] gave a protocol with O(sqrt{d}) communication for privately approximating the Hamming distance of two d-dimensional vectors. I will give a private protocol with polylog(d) communication for l_2. As a special case, this yields an exponential improvement over [FIMNSW] for the Hamming distance.Next I will consider the l_p distance, for p > 2. This problem is motivated by recent research in streaming algorithms, and has applications in database theory. I will give a 1-round protocol achieving optimal communication for this problem, up to logarithmic factors. It is easy to implement in the streaming model, and consequently resolves the main open question of a 1996 paper of Alon, Matias, and Szegedy.Joint work with Piotr Indyk (STOC 2005, TCC 2006).Biography: David Woodruff is a fifth-year PhD student at MIT. He received his master's in computer science, and B.S. degrees in both computer science and mathematics, all from MIT. He is interested in theoretical computer science, particularly algorithms, complexity theory, and cryptography.Hosted by David KempeRefreshments will be served.
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Nancy Levien
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CS Colloquium Lecture: Rachid Alami
Thu, Mar 29, 2007 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Title: A Robot That Aims to Serve Humans and Be Accepted By ThemProf. Rachid AlamiSenior Scientist at LAAS-CNRS, Toulouse, France. Abstract:We are conducting research toward the construction of a cognitive robots able to act in close interaction with humans and to serve as a companion in their daily life.
I will present several results developed in COGNIRON, a collaborative research project funded by the European Commission in the framework of the 'Beyond Robotics' workprogramme.
Cogniron research teams contribute to the study of the perceptual, representational, reasoning and learning capabilities of embodied robots in a human centred perspective.
More particularly, I will focus on issues that involve decisional interaction between a human and a robot that acts and moves in his close vicinity.Bio sketch:Prof. Rachid ALAMI is Senior Scientist at LAAS-CNRS, Toulouse, France. He received an engineer diploma in Computer Science in 1978 from ENSEEIHT, and a Ph.D in Robotics in 1983 from the University Paul Sabatier (Toulouse, France). He contributed and took important responsibilities in several national, European and international research and/or collaborative projects (EUREKA, ESPRIT, IST). His main research contributions fall in the fields of robot architectures, task and motion planning, manipulation, multi-robot cooperation and more generally robot decisional autonomy. He has also a substantial experience in robotics system integration and transfer operations.Host: Dr. Adriana Tapus
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Nancy Levien
