8 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.IR2023★ 8 cited
RL-MPCA: A Reinforcement Learning Based Multi-Phase Computation Allocation Approach for Recommender Systems
Jiahong Zhou, Shunhui Mao, Guoliang Yang +5
Recommender systems aim to recommend the most suitable items to users from a large number of candidates. Their computation cost grows as the number of user requests and the complex…
cs.LG2023★ 3 cited
Safe Offline Reinforcement Learning with Real-Time Budget Constraints
Qian Lin, Bo Tang, Zifan Wu +5
Aiming at promoting the safe real-world deployment of Reinforcement Learning (RL), research on safe RL has made significant progress in recent years. However, most existing works i…