In attempting to address real-life decision problems, where uncertainty about input data prevails, some kind of representation of imprecise information is important and several ha...
A fundamental task of data analysis is comprehending what distinguishes clusters found within the data. We present the problem of mining distinguishing sets which seeks to find s...
: Cross-match spatially clusters and organizes several astronomical point-source measurements from one or more surveys. Ideally, each object would be found in each survey. Unfortun...
Jim Gray, Alexander S. Szalay, Tamas Budavari, Rob...
Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
Given a set of patterns and a similarity measure between them, we will present an optimization framework to approximate a small subset, known as a canonical set, whose members clo...