Machine Learning based on the Regularized Least Square (RLS) model requires one to solve a system of linear equations. Direct-solution methods exhibit predictable complexity and s...
In this paper, independent component analysis (ICA) in a subband domain has been extended into a feed-forward network. The feed-forward network maximizes mutual independence of se...
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
We study a switch Markov chain on regular graphs, where switches are allowed only between links that are at distance 3; we call this the Flip. The motivation for studying the Flip...
Abstract. In the current paper, the Promedas model for internal medicine, developed by our team, is introduced. The model is based on up-todate medical knowledge and consists of ap...
Bastian Wemmenhove, Joris M. Mooij, Wim Wiegerinck...