Toh Kar-Ann

Accumulated Decoupled Learning with Gradient Staleness Mitigation for Convolutional Neural Networks

Gradient staleness is a major side effect in decoupled learning when training convolutional neural networks asynchronously. Existing methods that ignore this effect might result in reduced generalization and even divergence. In this paper, we propose an accumulated decoupled learning (ADL), which in…