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Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs.

, , и . ICLR, OpenReview.net, (2023)

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Andreas Pihera

Elisabeth Pihera

Jun Hu

Zaijun Hu

Hu Wang

 

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Optimal Multi-User Scheduling for the Unbalanced Full-Duplex Buffer-Aided Relay Systems., , , , и . IEEE Trans. Wirel. Commun., 18 (6): 3208-3221 (2019)RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch., , , , и . ICLR, OpenReview.net, (2023)Effective multi-user delay-constrained scheduling with deep recurrent reinforcement learning., , , , и . MobiHoc, стр. 1-10. ACM, (2022)Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation., , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 8971-9019. PMLR, (2022)Optimal Hybrid Full-Duplex/Half-Duplex Scheme of the Buffer Aided Relay System., , , и . CoRR, (2018)Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs., , и . ICLR, OpenReview.net, (2023)Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback., , , , , и . ICLR, OpenReview.net, (2024)Optimal Multi-User Scheduling of Buffer-Aided Relay Systems., , , и . ICC, стр. 1-6. IEEE, (2018)Mixed Sparsity Training: Achieving 4⨉ FLOP Reduction for Transformer Pretraining., , и . CoRR, (2024)Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training., , , , и . CoRR, (2024)