35 citations · 102 across the 10 of their papers we have counts for
10 papers
Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System
Bowei He, Xu He, Renrui Zhang +3
With the continuous increase of users and items, conventional recommender systems trained on static datasets can hardly adapt to changing environments. The high-throughput data req…
Collaborative Edge Caching: a Meta Reinforcement Learning Approach with Edge Sampling
Bowei He, Yinan Mao, Shiji Zhou +2
Current learning-based edge caching schemes usually suffer from dynamic content popularity, e.g., in the emerging short video platforms, users' request patterns shift significantly…
Mutually Guided Few-shot Learning for Relational Triple Extraction
Chengmei Yang, Shuai Jiang, Bowei He +2
Knowledge graphs (KGs), containing many entity-relation-entity triples, provide rich information for downstream applications. Although extracting triples from unstructured texts ha…
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…
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-…
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…
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…
Result Diversification in Search and Recommendation: A Survey
Haolun Wu, Yansen Zhang, Chen Ma +4
Diversifying return results is an important research topic in retrieval systems in order to satisfy both the various interests of customers and the equal market exposure of provide…
PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning
Xiangyang Zhu, Renrui Zhang, Bowei He +5
Large-scale pre-trained models have shown promising open-world performance for both vision and language tasks. However, their transferred capacity on 3D point clouds is still limit…
Collective Conditioned Reflex: A Bio-Inspired Fast Emergency Reaction Mechanism for Designing Safe Multi-Robot Systems
Bowei He, Zhenting Zhao, Wenhao Luo +1
A multi-robot system (MRS) is a group of coordinated robots designed to cooperate with each other and accomplish given tasks. Due to the uncertainties in operating environments, th…