Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
Recent papers and patents in iterative unsupervised learning have emphasized a new trend in clustering. It basically consists of penalizing solutions via weights on the instance po...
We study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure D. Given a finite set P of size n, our goal is to find a set C of size k such t...