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cs.LG2026
Policy Optimization in Hybrid Discrete-Continuous Action Spaces via Mixed Gradients
Matias Alvo, Daniel Russo, Yash Kanoria
We study reinforcement learning in hybrid discrete-continuous action spaces, such as settings where the discrete component selects a regime (or index) and the continuous component…
cs.LG2024
Optimizing Adaptive Experiments: A Unified Approach to Regret Minimization and Best-Arm Identification
Chao Qin, Daniel Russo
Practitioners conducting adaptive experiments often encounter two competing priorities: maximizing total welfare (or `reward') through effective treatment assignment and swiftly co…