Bayesian Inference and Maximum Entropy Methods in Science and Engineering—22nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Moscow, Idaho, 3-7 A

Papers from an August 2002 workshop reflect recent research on statistical inference, signal separation, physics applications, and inductive logic theory. Some specific topics include Chernoff's bound forms, a maximum entropy approach to a mean field theory for fluids, learning in the presence of input noise using the stochastic EM algorithm, and a Bayesian classification model for real-time intrusion detection. Other topics are wavelet domain image separation, logical and geometric inquiry, information geometry and prior selection, and hyperplane priors. There is no indexing other than an author list. Annotation (c) Book News, Inc., Portland, OR (booknews.com)