The K-means clustering problem seeks to partition the columns of a data matrix in subsets, such that columns in the same subset are ‘close’ to each other. The co-clustering pr...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos
Context-dependent word similarity can be measured over multiple cross-cutting dimensions. For example, lung and breath are similar thematically, while authoritative and superfici...
Cooperative robotic systems provide design and implementation challenges that are not easy to solve. This paper describes a parallel implementation for evolving cooperative roboti...
Stereotypes and clustering are some techniques for creating user models from user behavior. Yet, they possess important risks as users actions could be misinterpreted or users coul...
Abstract. Bayesian approaches to density estimation and clustering using mixture distributions allow the automatic determination of the number of components in the mixture. Previou...