Game Theory & Clustering
published: April 1, 2009, recorded: February 2009, views: 2197
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
The course will provide an overview of recent work on pairwise data clustering which has lead to establish intriguing connections between unsupervised learning and (evolutionary) game theory. The framework is centered around the notion of a "dominant set," a novel graph-theoretic concept which generalizes that of a maximal clique to edge-weighted graphs. Algorithms inspired from evolutionary game theory, and applications in computer vision and pattern recognition will be discussed.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !