אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

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.