We present a novel linear clustering framework (DIFFRAC) which relies on a linear discriminative cost function and a convex relaxation of a combinatorial optimization problem. The...
In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining p...
Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Ka...
Abstract. We propose an association analysis-based strategy for exploration of multi-attribute spatial datasets possessing naturally arising classification. Proposed strategy, EST...
Tomasz F. Stepinski, Josue Salazar, Wei Ding 0003,...
In many vision problems, instead of having fully labeled training data, it is easier to obtain the input in small groups, where the data in each group is constrained to be from th...
Several kernel algorithms have recently been proposed for nonlinear discriminant analysis. However, these methods mainly address the singularity problem in the high dimensional fe...