Game Theory & Clustering
author: Marcello Pelillo,
University Ca' Foscari
published: April 1, 2009, recorded: February 2009, views: 14659
published: April 1, 2009, recorded: February 2009, views: 14659
Slides
Related content
Report a problem or upload files
If 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.
Description
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 page
Would you like to put a link to this lecture on your homepage?Go ahead! Copy the HTML snippet !
Write your own review or comment: