This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Contact map prediction is of great interest for its application in fold recognition and protein 3D structure determination. In this paper we present a contact-map prediction algor...
In the design of many proactive routing protocols for MANETs, it is often assumed that topology information is disseminated instantly and error free. Exceptions include hazysighte...
There is an increased dominance of intra-die process variations, creating a need for an accurate and fast statistical timing analysis. Most of the recent proposed approaches assum...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...