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cs.LG2024
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
Yu Chen, Jiatai Huang, Yan Dai +1
In this paper, we present a novel algorithm, uniINF, for the Heavy-Tailed Multi-Armed Bandits (HTMAB) problem, demonstrating robustness and adaptability in both stochastic and adve…
cs.LG2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation
Yu Chen, Xiangcheng Zhang, Siwei Wang +1
In the realm of reinforcement learning (RL), accounting for risk is crucial for making decisions under uncertainty, particularly in applications where safety and reliability are pa…
cs.LG2024
Provably Efficient Partially Observable Risk-Sensitive Reinforcement Learning with Hindsight Observation
Tonghe Zhang, Yu Chen, Longbo Huang
This work pioneers regret analysis of risk-sensitive reinforcement learning in partially observable environments with hindsight observation, addressing a gap in theoretical explora…