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cs.LG2025
SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes
Xuyuan Xiong, Pedro Chumpitaz-Flores, Kaixun Hua +1
Interpretable reinforcement learning policies are essential for high-stakes decision-making, yet optimizing decision tree policies in Markov Decision Processes (MDPs) remains chall…
cs.LG2025
Continuous Q-Score Matching: Diffusion Guided Reinforcement Learning for Continuous-Time Control
Chengxiu Hua, Jiawen Gu, Yushun Tang
Reinforcement learning (RL) has achieved significant success across a wide range of domains, however, most existing methods are formulated in discrete time. In this work, we introd…
cs.LG2025
CatBOX: A Categorical-Continuous Bayesian Optimization with Spectral Mixture Kernels for Accelerated Catalysis Experiments
Changquan Zhao, Yi Zhang, Zhuo Li +3
Identifying optimal catalyst compositions and reaction conditions is central in catalysis research, yet remains challenging due to the vast multidimensional design spaces encompass…