Emergence of the web and online computing applications gave rise to rich large scale social activity data. One of the principal challenges then is to build models and understandin...
Abstract. Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology an...
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishn...
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
In order to structure a gene network, a score-based approach is often used. A score-based approach, however, is problematic because by assuming a probability distribution, one is ...
Abstract. We introduce a new genetic algorithm approach for learning a Bayesian network structure from data. Our method is capable of learning over all node orderings and structure...