Maximum volume clustering: a new discriminative clustering approach

Gang Niu, Bo Dai, Lin Shang, Masashi Sugiyama
2013 Journal of machine learning research  
The large volume principle proposed by Vladimir Vapnik, which advocates that hypotheses lying in an equivalence class with a larger volume are more preferable, is a useful alternative to the large margin principle. In this paper, we introduce a new discriminative clustering model based on the large volume principle called maximum volume clustering (MVC), and then propose two approximation schemes to solve this MVC model: A soft-label MVC method using sequential quadratic programming and a
more » ... abel MVC method using semi-definite programming, respectively. The proposed MVC is theoretically advantageous for three reasons. The optimization involved in hardlabel MVC is convex, and under mild conditions, the optimization involved in soft-label MVC is akin to a convex one in terms of the resulting clusters. Secondly, the soft-label MVC method pos- * .
dblp:journals/jmlr/NiuDSS13 fatcat:cvo43atwwfdo7mupp452uskocu