A stochastically motivated random initialization of pattern classifying MLPs

Abstract

In this contribution, a new stochastically motivated random weight initialization scheme for pattern classifying Multi-Layer Perceptrons (MLPs) is presented. Its first aim is to ensure that all training examples and all nodes have an equal opportunity to contribute to the improvement of the network during the Error Back-Propagation (EBP) training. In… (More)
DOI: 10.1007/BF00417786

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