82 citations · 101 across the 10 of their papers we have counts for
4 papers · 1 filter
Multi-Interest Recommendation: A Survey
Zihao Li, Qiang Chen, Lixin Zou +2
Existing recommendation methods often struggle to model users' multifaceted preferences due to the diversity and volatility of user behavior, as well as the inherent uncertainty an…
Efficient and Robust Regularized Federated Recommendation
Langming Liu, Wanyu Wang, Xiangyu Zhao +9
Recommender systems play a pivotal role across practical scenarios, showcasing remarkable capabilities in user preference modeling. However, the centralized learning paradigm predo…
One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems
Zuoli Tang, Zhaoxin Huan, Zihao Li +6
Sequential recommendation systems aim to predict users' next likely interaction based on their history. However, these systems face data sparsity and cold-start problems. Utilizing…
A Survey on Reinforcement Learning for Recommender Systems
Yuanguo Lin, Yong Liu, Fan Lin +5
Recommender systems have been widely applied in different real-life scenarios to help us find useful information. In particular, Reinforcement Learning (RL) based recommender syste…