Han-Wen Ma

Percolation of Data Constraints and Reorganization of Boolean Function States in Parity Learning

We study how a neural network reorganizes its learned function as training proceeds and as previously unseen parity data accumulate. The trained model is itself a Boolean function on binary strings of finite length. We then evaluate it on all data, inside and outside the training set, and read off its complete sign tab...