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Locally Bayesian Learning with Applications to Retrospective Revaluation and Highlighting
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Kruschke, John K. – Psychological Review, 2006
A scheme is described for locally Bayesian parameter updating in models structured as successions of component functions. The essential idea is to back-propagate the target data to interior modules, such that an interior component's target is the input to the next component that maximizes the probability of the next component's target. Each layer…
Descriptors: Bayesian Statistics, Models, Probability, Associative Learning