UNIQUENESS OF WEIGHTS FOR NEURAL NETWORKS

Abstract

In most applications dealing with learning and pattern recognition, neural nets are employed as models whose parameters, or “weights, ” must be fit to training data. Gradient descent and other algorithms are used in order to minimize an error functional, which penalizes mismatches between the