3 citations · 8 across the 22 of their papers we have counts for
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cs.LG2025
Maximum Total Correlation Reinforcement Learning
Bang You, Puze Liu, Huaping Liu +2
Simplicity is a powerful inductive bias. In reinforcement learning, regularization is used for simpler policies, data augmentation for simpler representations, and sparse reward fu…
cs.LG2024★ 1 cited
Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning
Jonas Günster, Puze Liu, Jan Peters +1
Safety is one of the key issues preventing the deployment of reinforcement learning techniques in real-world robots. While most approaches in the Safe Reinforcement Learning area d…
cs.LG2022★ 1 cited
Dimensionality Reduction and Prioritized Exploration for Policy Search
Marius Memmel, Puze Liu, Davide Tateo +1
Black-box policy optimization is a class of reinforcement learning algorithms that explores and updates the policies at the parameter level. This class of algorithms is widely appl…