A neural network with fixed topology can be regarded as a parametrization of functions, which decides on the correlations between functional variations when parameters are adapted...
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...
This paper presents an application of multiple kernels like Kernel Basis to the Relevance Vector Machine algorithm. The framework of kernel machines has been a source of many works...
Mapping brain activity patterns in external actions has been studied in recent decades and is the base of a brain-computer interface. This type of interface is extremely useful for...
Alexandre Ormiga G. Barbosa, David Ronald A. Diaz,...
—In this paper, we proposed a reduced polynomial neural swarm net (RPNSN) for the task of classification. Classification task is one of the most studied tasks of data mining. In ...