8 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.LG2026
Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization
Yang Bai, Kaiyuan Liu, Ziyuan Zhuang +5
Complex reinforcement learning environments frequently employ multi-task and mixed-reward formulations. In these settings, heterogeneous reward distributions and correlated reward…
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
HiBid: A Cross-Channel Constrained Bidding System with Budget Allocation by Hierarchical Offline Deep Reinforcement Learning
Hao Wang, Bo Tang, Chi Harold Liu +7
Online display advertising platforms service numerous advertisers by providing real-time bidding (RTB) for the scale of billions of ad requests every day. The bidding strategy hand…