6 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 6 cited
Benchmarking Neural Network Training Algorithms
George E. Dahl, Frank Schneider, Zachary Nado +22
Training algorithms, broadly construed, are an essential part of every deep learning pipeline. Training algorithm improvements that speed up training across a wide variety of workl…
cs.LG2022
Optimizing Data Collection in Deep Reinforcement Learning
James Gleeson, Daniel Snider, Yvonne Yang +3
Reinforcement learning (RL) workloads take a notoriously long time to train due to the large number of samples collected at run-time from simulators. Unfortunately, cluster scale-u…