Christopher Marquis

An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn

This paper introduces the notion of “Initial Alignment” (INAL) between a neural network at initialization and a target function. It is proved that if a network and a Boolean target function do not have a noticeable INAL, then noisy gradient descent with normalized i.i.d. initialization will not lear…