The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Mass-produced goods tend to be highly standardized in order to maximize manufacturing efficiencies. Some high-value goods with limited production quantities remain much less stand...
In the present study, an efficient strategy for retrieving texture images from large texture databases is introduced and studied within a distributional-statistical framework. Our...
Vasileios K. Pothos, Christos Theoharatos, George ...
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...
We propose a novel utterance comparison model based on probability theory and factor analysis that computes the likelihood of two speech utterances originating from the same speak...