Marcello Pelillo (University of Venice, Italy
Thursday, 24.6.2010, 11:30
Contrary to the vast majority of approaches to clustering, which view
the problem as one of partitioning a set of observations into coherent
classes, thereby obtaining the clusters as a by-product of the
partitioning process, we propose to reverse the terms of the problem and
attempt instead to derive a rigorous formulation of the very notion of
a cluster. In our endeavor to provide an answer to this question, we
found that game theory offers a very elegant and general perspective
that serves well our purposes.
Accordingly, we formulate the clustering problem as a non-cooperative
"clustering game". Within this context, the notion of a cluster turns
out to be equivalent to a classical equilibrium concept from
(evolutionary) game theory. Applications to computer vision problems and
generalizations of the proposed idea will be discussed.