Several advanced techniques have been proposed for data clustering and many of them have been applied to gene expression data, with partial success. The high dimensionality and the...
This paper introduces improved methodology to triangulate dynamic graphical models and dynamic Bayesian networks (DBNs). In this approach, a standard DBN template can be modified...
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms correspo...
— This paper is about collision avoidance of crowd robots. For this purpose a model of potential field is proposed. This potential field, generated by a neural network, is uniq...
Recent research in decision theoretic planning has focussedon making the solution of Markov decision processes (MDPs) more feasible. We develop a family of algorithms for structur...
Craig Boutilier, Ronen I. Brafman, Christopher W. ...