Multimodal optimization problems consist in detecting all global and local optima of a problem. A new evolutionary approach to multimodal optimization called Roaming technique (RO...
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...
Multiclass problems with binary SVM classifiers are commonly treated as a decomposition in several binary sub-problems. An open question is how to properly tune all these sub-prob...
The paper presents a compiler framework for analyzing and optimizing OpenMP programs. The framework includes Parallel Control Flow Graph and Parallel Data Flow equations based on t...