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Events for March 22, 2011
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GTHB Seminar
Tue, Mar 22, 2011 @ 12:00 PM - 01:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Prof. Eric Friedman, Cornell University
Talk Title: Bargaining Theory in the Cloud
Abstract: The axiomatic theory of bargaining solutions was initiated by John Nash with his seminal paper in 1950 and has a long and mostly mathematical history. Surprisingly, it arises naturally in a variety of allocation problems arising in cloud computing. For example, the second most famous bargaining solution, the Kalai-Smorodinsky solution, is the outcome of a simple water filling algorithm used in the Mesos Platform and has many strong properties in that setting, including incentive compatibility and fairness. In this talk, he will explore these connections for a variety of cloud computing problems and show how axiomatic bargaining theory can be used to analyze allocation problems in the cloud and conversely how cloud computing sheds new light on axiomatic bargaining theory.
This talk is based on joint work with Ali Ghodsi, Scott Shenker and Ion Stoica.
Biography: Eric Friedman is Associate Professor of Operations Research and Information Engineering at Cornell University and a Senior Research Scientist at the International Computer Science Institute at Berkeley (ICSI). His research interests include applications of game theory and complex network theory to computer science and cognitive neuroscience.
Host: Prof. Yu-Han Chang
More Info: http://gthb.usc.edu/Seminars/Location: Seeley Wintersmith Mudd Memorial Hall (of Philosophy) (MHP) - 101
Audiences: Everyone Is Invited
Contact: Kanak Agrawal
Event Link: http://gthb.usc.edu/Seminars/
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Annual George Bekey Keynote Lecture 2011
Tue, Mar 22, 2011 @ 04:00 PM - 06:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Prof. Michael I. Jordan, University of California, Berkeley
Talk Title: Completely Random Measures for Bayesian Nonparametrics
Abstract: Computer Science has historically been strong on data structures and weak on inference from data, whereas Statistics has historically been weak on data structures and strong on inference from data. One way to draw on the strengths of both disciplines is to pursue the study of "inferential methods for data structures", i.e., methods that update probability distributions on recursively-defined objects such as trees, graphs, grammars and function calls. This is accommodated in the world of "Bayesian non parametrics", where prior and posterior distributions are allowed to be general stochastic processes. Both statistical and computational considerations lead one to certain classes of stochastic processes, and these tend to have interesting connections to combinatorics. I will focus on Bayesian non parametric modeling based on completely random measures, giving examples of how recursions based on these measures lead to useful models in several applied problem domains, including protein structural modeling, natural language processing, computational vision, and statistical genetics.
Biography: Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. His research in recent years has focused on Bayesian nonparametric analysis, probabilistic graphical models, spectral methods, kernel machines and applications to problems in signal processing, statistical genetics, computational biology, information retrieval and natural language processing. Prof. Jordan was named to the National Academy of Sciences (NAS) in 2010 and the National Academy of Engineering (NAE) in 2010. He is a Fellow of the American Association for the Advancement of Science, the IMS, the ACM, and the IEEE.
Refreshments will be served at the Gerontology (GER) courtyard at 4 pm. Talk begins in GER Auditorium at 4:30pm.
Host: Prof. Fei Sha
Location: Ethel Percy Andrus Gerontology Center (GER) - Auditorium
Audiences: Everyone Is Invited
Contact: Kanak Agrawal
