A BP-based algorithm for performing Bayesian inference in large perceptron-type networks

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 3244, Issue , 2004, Pages 479-493

  Kabashima, Yoshiyuki ^a   Uda, Shinsuke ^a  

^a TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL COMPLEXITY; INFERENCE ENGINES; LEARNING SYSTEMS; MOBILE TELECOMMUNICATION SYSTEMS; STATISTICAL MECHANICS; BAYESIAN NETWORKS; COMPUTATION THEORY; NETWORK LAYERS;

BAYESIAN INFERENCE; BELIEF PROPAGATION (BP); CONDITIONAL DISTRIBUTION; ITERATIVE ALGORITHM; APPROXIMATE BAYESIAN INFERENCE; BAYESIAN APPROACHES; CENTRAL LIMIT THEOREM; FEED-FORWARD NETWORK; LAW OF LARGE NUMBERS; MOBILE COMMUNICATIONS SYSTEMS; OPTIMAL PERFORMANCE; PERCEPTRON-TYPE NETWORKS;

FEEDFORWARD NEURAL NETWORKS; INFERENCE ENGINES;

EID: 22944440371     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-30215-5_36     Document Type: Conference Paper

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