Optimal Multi-User Scheduling of Buffer-Aided Relay Systems. - Pihe Hu; Cheng Li 004; Dingjie Xu; Bin Xia 001 (ICC, 2018)

Optimal Hybrid Full-Duplex/Half-Duplex Scheme of the Buffer Aided Relay System. - Cheng Li 004; Bin Xia 001; Pihe Hu; Yao Yao 001 (CoRR, 2018)

Optimal Multi-User Scheduling for the Unbalanced Full-Duplex Buffer-Aided Relay Systems. - Cheng Li 004; Pihe Hu; Yao Yao 001; Bin Xia 001; Zhiyong Chen 002 (IEEE Trans. Wirel. Commun., 2019)

Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation. - Pihe Hu; Yu Chen 074; Longbo Huang (ICML, 2022)

Effective multi-user delay-constrained scheduling with deep recurrent reinforcement learning. - Pihe Hu; Ling Pan; Yu Chen 074; Zhixuan Fang; Longbo Huang (MobiHoc, 2022)

RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch. - Yiqin Tan; Pihe Hu; Ling Pan; Longbo Huang (CoRR, 2022)

Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs. - Pihe Hu; Yu Chen 074; Longbo Huang (ICLR, 2023)

RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch. - Yiqin Tan; Pihe Hu; Ling Pan; Jiatai Huang; Longbo Huang (ICLR, 2023)

Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback. - Yu Chen 074; Yihan Du; Pihe Hu; Siwei Wang 002; Desheng Wu; Longbo Huang (ICLR, 2024)

Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training. - Pihe Hu; Shaolong Li; Zhuoran Li; Ling Pan; Longbo Huang (NeurIPS, 2024)

Mixed Sparsity Training: Achieving 4⨉ FLOP Reduction for Transformer Pretraining. - Pihe Hu; Shaolong Li; Longbo Huang (CoRR, 2024)

Multi-User Delay-Constrained Scheduling With Deep Recurrent Reinforcement Learning. - Pihe Hu; Yu Chen 074; Ling Pan; Zhixuan Fang; Fu Xiao 001; Longbo Huang (IEEE/ACM Trans. Netw., 2024)

Mixed Sparsity Training: Achieving 4× FLOP Reduction for Transformer Pretraining. - Pihe Hu; Shaolong Li; Xun Wang 013; Longbo Huang (Trans. Mach. Learn. Res., 2025)