2 papers
cs.IR2026
Federated Learning and Unlearning for Recommendation with Personalized Data Sharing
Liang Qu, Jianxin Li, Wei Yuan +4
Federated recommender systems (FedRS) have emerged as a paradigm for protecting user privacy by keeping interaction data on local devices while coordinating model training through…
cs.IR2024
CADRL: Category-aware Dual-agent Reinforcement Learning for Explainable Recommendations over Knowledge Graphs
Shangfei Zheng, Hongzhi Yin, Tong Chen +3
Knowledge graphs (KGs) have been widely adopted to mitigate data sparsity and address cold-start issues in recommender systems. While existing KGs-based recommendation methods can…