Microsoft Corporation
COMPRESSING WEIGHTS FOR DISTRIBUTED NEURAL NETWORKS

Abstract:

Embodiments of the present disclosure include systems and methods for compressing weights for distributed neural networks. In some embodiments, a first network comprising a first set of weights is trained using a set of training data. A second network comprising a second set of weights is trained using the set of training data. A number of weights in the first set of weights is greater than a number of weights in the second set of weights. The first set of weights are adjusted based on a first loss determined by the first network and a second loss determined by the second network. The second set of weights are adjusted based on the first loss determined by the first network and the second loss determined by the second network. Values of the second set of weights are sent to a computing system.