Abstract. It has been recently demonstrated that the classical EM algorithm for learning Gaussian mixture models can be successfully implemented in a decentralized manner by resort...
Nikos A. Vlassis, Yiannis Sfakianakis, Wojtek Kowa...
We discuss a retrieval model in which the task is to complete a sentence, given an initial fragment, and given an application specific document collection. This model is motivate...
Clustering is an unsupervised learning task which provides a decomposition of a dataset into subgroups that summarize the initial base and give information about its structure. We ...
This work presents the application of theory revision to the design of distributed databases to automatically revise a heuristic-based algorithm (called analysis algorithm) through...
Unit Clustering is the problem of dividing a set of points from a metric space into a minimal number of subsets such that the points in each subset are enclosable by a unit ball. W...