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cs.LG2024
Beyond the Boundaries of Proximal Policy Optimization
Charlie B. Tan, Edan Toledo, Benjamin Ellis +2
Proximal policy optimization (PPO) is a widely-used algorithm for on-policy reinforcement learning. This work offers an alternative perspective of PPO, in which it is decomposed in…
cs.LG2024
On the Limitations of Fractal Dimension as a Measure of Generalization
Charlie B. Tan, Inés García-Redondo, Qiquan Wang +2
Bounding and predicting the generalization gap of overparameterized neural networks remains a central open problem in theoretical machine learning. There is a recent and growing bo…