Population Based Training as a Service
Abstract
Population Based Training (PBT) is a recent approach that jointly optimizes neural network weights and hyperparameters which periodically copies weights of the best performers and mutates hyperparameters during training. We present in this extended abstract a generalized black-box service framework for Population Based Training. We argue that the black-box PBT service design has benefits in system scalability and required engineering effort. We perform a case study on WaveNet speech synthesis to demonstrate the effectiveness of our PBT service.
Research Areas
