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...
This paper introduces subchromosome representations to the linkage learning genetic algorithm (LLGA). The subchromosome representation is utilized for effectively lowering the num...
A central issue in relational learning is the choice of an appropriate bias for limiting first-order induction. The purpose of this study is to circumvent this issue within a unifo...
Abstract. In this paper we investigate the feed-forward learning problem. The well-known ill-conditioning which is present in most feed-forward learning problems is shown to be the...
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...
Pierre Machart, Thomas Peel, Liva Ralaivola, Sandr...