9 citations · 13 across the 8 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.LG2022★ 9 cited
Effective Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning
Pihe Hu, Ling Pan, Yu Chen +2
Multi-user delay constrained scheduling is important in many real-world applications including wireless communication, live streaming, and cloud computing. Yet, it poses a critical…
cs.LG2022★ 2 cited
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
Pihe Hu, Yu Chen, Longbo Huang
We study reinforcement learning with linear function approximation where the transition probability and reward functions are linear with respect to a feature mapping $\boldsymbolϕ(…
cs.LG2022★ 1 cited
RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
Yiqin Tan, Pihe Hu, Ling Pan +2
Training deep reinforcement learning (DRL) models usually requires high computation costs. Therefore, compressing DRL models possesses immense potential for training acceleration a…