Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Bayesian networks (BN) are particularly well suited to capturing vague and uncertain knowledge. However, the capture of this knowledge and associated reasoning from human domain e...
Jonathan D. Pfautz, Zach Cox, Geoffrey Catto, Davi...
Intelligent agents have to be able to merge informational inputs received from different sources in a coherent and rational way. Several proposals have been made for information m...
Samir Chopra, Aditya K. Ghose, Thomas Andreas Meye...
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
Based on speculations coming from statistical mechanics and the conjectured existence of critical states, I propose a simple heuristic in order to control the mutation probability...