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Bayesian Backpropagation Over I-O Functions Rather Than Weights

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  • David H. Wolpert

Abstract

The conventional Bayesian justification for backprop is that it finds the MAP weight vector. As this paper shows, to find the MAP i-o function instead, one must add a correction term to backprop. That term biases one towards i-o functions with small description lengths, and in particular favors (some kinds of) feature-selection, pruning, and weight-sharing. This can be viewed as an {\it a priori} argument in favor of those techniques.

Suggested Citation

  • David H. Wolpert, 1994. "Bayesian Backpropagation Over I-O Functions Rather Than Weights," Working Papers 94-04-019, Santa Fe Institute.
    • Handle: RePEc:wop:safiwp:94-04-019
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    Cited by:

    1. David H. Wolpert & Charles E.M. Strauss, 1995. "What Bayes Has to Say About the Evidence Procedure," Working Papers 95-02-026, Santa Fe Institute.

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