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 ...
This paper describes the study conducted to design and evaluate a two-level on-line scheduler to dynamically schedule a stream of sequential and multi-threaded batch jobs on large...
Marco Pasquali, Ranieri Baraglia, Gabriele Capanni...
Abstract. We define a novel, basic, unsupervised learning problem learning the the lowest density homogeneous hyperplane separator of an unknown probability distribution. This task...
: Wireless sensor networks require energy efficient routing protocols owing to limited resource on the sensor node. In this paper, we develop optimal distance geographic routing (O...
Distributed data mining deals with the problem of data analysis in environments with distributed data, computing nodes, and users. Peer-to-peer computing is emerging as a new dist...
Souptik Datta, Kanishka Bhaduri, Chris Giannella, ...