ICML "linear function approximation" Papers

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Averaging $n$-step Returns Reduces Variance in Reinforcement Learning

Brett Daley, Martha White, Marlos C. Machado

ICML 2024oralarXiv:2402.03903

Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization

Yihan Du, Anna Winnicki, Gal Dalal et al.

ICML 2024posterarXiv:2402.10342

Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret

Han Zhong, Jiachen Hu, Yecheng Xue et al.

ICML 2024posterarXiv:2302.10796