Based on rank-1 update, Sparse Bayesian Learning Algorithm (SBLA) is proposed. SBLA has the advantages of low complexity and high sparseness, being very suitable for large scale pr...
This paper addresses the issue of operationalising guidelines for IOS planning. The authors explore the usefulness of Triple Loop Learning in light of the IOS development experien...
Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of...
We consider two layered binary state neural networks in which cellular topographic self-organization occurs under correlational learning. The main result is that for separable inpu...
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...