4 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.LG2019★ 4 cited
Demon: Improved Neural Network Training with Momentum Decay
John Chen, Cameron Wolfe, Zhao Li +1
Momentum is a widely used technique for gradient-based optimizers in deep learning. In this paper, we propose a decaying momentum (\textsc{Demon}) rule. We conduct the first large-…
stat.ML2018★ 2 cited
Exploration of Numerical Precision in Deep Neural Networks
Zhaoqi Li, Yu Ma, Catalina Vajiac +1
Reduced numerical precision is a common technique to reduce computational cost in many Deep Neural Networks (DNNs). While it has been observed that DNNs are resilient to small erro…