Adobe Inc.
Resource-Aware Training for Neural Networks

Last updated:

Abstract:

In implementations of resource-aware training for neural network, one or more computing devices of a system implement an architecture optimization module for monitoring parameter utilization while training a neural network. Dead neurons of the neural network are identified as having activation scales less than a threshold. Neurons with activation scales greater than or equal to the threshold are identified as survived neurons. The dead neurons are converted to reborn neurons by adding the dead neurons to layers of the neural network having the survived neurons. The reborn neurons are prevented from connecting to the survived neurons for training the reborn neurons.

Status:
Application
Type:

Utility

Filling date:

22 Jan 2019

Issue date:

23 Jul 2020