most citedDynamically Expandable Graph Convolution for Streaming Recommendation

35 citations · 44 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2023

Sim2Rec: A Simulator-based Decision-making Approach to Optimize Real-World Long-term User Engagement in Sequential Recommender Systems

Xiong-Hui Chen, Bowei He, Yang Yu +5

Long-term user engagement (LTE) optimization in sequential recommender systems (SRS) is shown to be suited by reinforcement learning (RL) which finds a policy to maximize long-term…

cs.CV20237 cited

Not All Features Matter: Enhancing Few-shot CLIP with Adaptive Prior Refinement

Xiangyang Zhu, Renrui Zhang, Bowei He +4

The popularity of Contrastive Language-Image Pre-training (CLIP) has propelled its application to diverse downstream vision tasks. To improve its capacity on downstream tasks, few-…

cs.IR202335 cited

Dynamically Expandable Graph Convolution for Streaming Recommendation

Bowei He, Xu He, Yingxue Zhang +2

Personalized recommender systems have been widely studied and deployed to reduce information overload and satisfy users' diverse needs. However, conventional recommendation models…

cs.AI20232 cited

Towards Skilled Population Curriculum for Multi-Agent Reinforcement Learning

Rundong Wang, Longtao Zheng, Wei Qiu +7

Recent advances in multi-agent reinforcement learning (MARL) allow agents to coordinate their behaviors in complex environments. However, common MARL algorithms still suffer from s…

cs.SI2016

Expenditure Aware Rating Prediction for Recommendation

Chuan Shi, Bowei He, Menghao Zhang +2

The rating score prediction is widely studied in recommender system, which predicts the rating scores of users on items through making use of the user-item interaction information.…