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Publications

Here is a full list of my publications:

Journals

  1. Pihe Hu, Yu Chen, Ling Pan, Zhixuan Fang, Fu Xiao, Longbo Huang. “Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning.” IEEE/ACM Transactions on Networking (TON), [IEEE Xplore]

  2. Cheng Li, Pihe Hu, Yao Yao, Bin Xia, Zhiyong Chen. “Optimal Multi-User Scheduling for the Unbalanced Full-Duplex Buffer-Aided Relay Systems,” IEEE Transactions on Wireless Communications (TWC), 18(6) pp. 3208-3221 (2019). [pdf]

Conferences

  1. Yu Chen, Yihan Du, Pihe Hu, Longbo Huang. “Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs.” International Conference on Learning Representations (ICLR), 2024 [OpenReview]

  2. Pihe Hu*, Yu Chen*, Longbo Huang. “Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs.” International Conference on Learning Representations (ICLR), 2023 [OpenReview] (* indicates joint first author)

  3. Yiqin Tan*, Pihe Hu*, Ling Pan, Longbo Huang. “RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch.” International Conference on Learning Representations (ICLR), 2023 [OpenReview] (Spotlight) (* indicates joint first author)

  4. Pihe Hu, Ling Pan, Yu Chen, Zhixuan Fang and Longbo Huang。 “Effective Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning.” International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc), 2022. [pdf]

  5. Pihe Hu, Yu Chen, Longbo Huang. “Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation.” International Conference on Machine Learning (ICML), pp. 8971-9019. PMLR, 2022. [pdf] (Erratum: an issue in building the over-optimistic value function is addressed by the ‘‘rare-switching’’ mechanism in [He et al. 2022.], and the fixed version is given in [arxiv])

  6. Pihe Hu, Cheng Li, Dingjie Xu, Bin Xia. “Optimal multi-user scheduling of buffer-aided relay systems.” IEEE International Conference on Communications (ICC), pp. 1-6, 2018. [pdf]

Preprints

  1. Yu Chen, Yihan Du, Pihe Hu, Siwei Wang, Longbo Huang. “Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation.” arXiv preprint arXiv:2307.02842 (2023). [pdf]

Thesis

  1. Pihe Hu: “Multi-armed Bandits in Versatile Settings”, BsC thesis, Shanghai Jiao Tong University (SJTU), 2019. [pdf]

Course Projects

  1. Pihe Hu. “Optimal resource allocation in edge computing for mobile blockchain by genetic algorithm” Course Projects of Mobile Internet (EE447), Shanghai Jiao Tong University, 2018 [pdf]