Comparing Biases for Minimal Network Construction with Back-Propagation

This approach can be used to (a) dynamically select the number of hidden units. The method Rumelhart suggests involves adding penalty terms to the usual error function. In this paper we introduce Rumelhart·s minimal networks idea and compare two possible biases on the weight search space. These biases are compared in both simple counting problems and a speech recognition problem.