3 citations · 6 across the 8 of their papers we have counts for
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cs.LG2023★ 2 cited
Clipped-Objective Policy Gradients for Pessimistic Policy Optimization
Jared Markowitz, Edward W. Staley
To facilitate efficient learning, policy gradient approaches to deep reinforcement learning (RL) are typically paired with variance reduction measures and strategies for making lar…
cs.LG2022
Triangular Dropout: Variable Network Width without Retraining
Edward W. Staley, Jared Markowitz
One of the most fundamental design choices in neural networks is layer width: it affects the capacity of what a network can learn and determines the complexity of the solution. Thi…
cs.LG2021★ 1 cited
The AI Arena: A Framework for Distributed Multi-Agent Reinforcement Learning
Edward W. Staley, Corban G. Rivera, Ashley J. Llorens
Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscap…