Evolutionary games and data clustering

Marcello Pelillo (University of Venice)

NICTA SML SEMINAR Game Theory in Pattern Recognition and Machine Learning

DATE: 2011-07-28
TIME: 11:00:00 - 12:00:00
LOCATION: NICTA, 7 London Circuit, Seminar Room, Ground Floor
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ABSTRACT:
This is the second of three talks on "Game Theory in Pattern Recognition and Machine Learning". The development of game theory in the early 1940as by John von Neumann was a reaction against the then dominant view that problems in economic theory can be formulated using standard methods from optimization theory. Indeed, most real- world economic problems typically involve conflicting interactions among decision-making agents that cannot be adequately captured by a single (global) objective function, thereby requiring a different, more sophisticated treatment. Accordingly, the main point made by game theorists is to shift the emphasis from optimality criteria to equilibrium conditions. As it provides an abstract theoretically-founded framework to elegantly model complex scenarios, game theory has found a variety of applications not only in economics and, more generally, social sciences but also in different fields of engineering and information technologies. In particular, in the past there have been various attempts aimed at formulating problems in computer vision, pattern recognition and machine learning from a game-theoretic perspective and, with the recent development of algorithmic game theory, the interest in these communities around game-theoretic models and algorithms is growing at a fast pace.

The goal of these three talks is to offer an introduction to the basic concepts of game theory and to provide an overview of the work we're currently doing in my group on the use of game-theoretic models in pattern recognition and machine learning. I shall assume no pre-existing knowledge of game theory by the audience, thereby making the talks self-contained and understandable by a non-expert.

BIO:
Marcello Pelillo joined the faculty of the University of Bari, Italy, as an Assistant professor of computer science in 1991. Since 1995, he has been with the University of Venice, Italy, where he is currently a Professor of Computer Science and has served from 2004 to 2010 as the Chair of the board of studies of the Computer Science School. He held visiting research positions at Yale University, the University College London, McGill University, the University of Vienna, York University (UK), and the National ICT Australia (NICTA). He has published more than a hundred technical papers in refereed journals, handbooks, and conference proceedings in the areas of computer vision, pattern recognition and neural computation. He has been actively involved in the organization of several scientific meetings including the NIPS*99 Workshop on "Complexity and Neural Computation: The Average and the Worst Case," the 2008 International Workshop on Computer Vision (http://dsi.unive.it/~iwcv) and the ICML 2010 Workshop on "Learning in non-(geo)metric spaces." In 1997, he co-established a new series of international conferencess devoted to energy minimization methods in computer vision and pattern recognition (EMMCVPR), which has now reached the eight edition. He serves (or has served) on the editorial board for the journals IEEE Transactions on Pattern Analysis and Machine Intelligence and Pattern Recognition, and is regularly on the program committees of the major international conferences and workshops of his fields. He is (or has been) scientific coordinator of several research projects, including SIMBAD, an EU-FP7 project devoted to similarity-based pattern analysis and recognition (http://simbad-fp7.eu). Prof. Pelillo is a Fellow of the IAPR and a Senior Member of the IEEE.