Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization met...
Georg Schneider, Heiko Wersing, Bernhard Sendhoff,...
Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportu...
As an extension of Bayesian network, module network is an appropriate model for inferring causal network of a mass of variables from insufficient evidences. However learning such ...