2 citations · 5 across the 13 of their papers we have counts for
4 papers · 1 filter
Multimodal-enhanced Federated Recommendation: A Group-wise Fusion Approach
Chunxu Zhang, Weipeng Zhang, Guodong Long +3
Federated Recommendation (FR) is a new learning paradigm to tackle the learn-to-rank problem in a privacy-preservation manner. How to integrate multi-modality features into federat…
Distilling A Universal Expert from Clustered Federated Learning
Zeqi Leng, Chunxu Zhang, Guodong Long +2
Clustered Federated Learning (CFL) addresses the challenges posed by non-IID data by training multiple group- or cluster-specific expert models. However, existing methods often ove…
A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation
Zhiwei Li, Guodong Long, Chunxu Zhang +3
Integrating Foundation Models (FMs) into recommendation systems is an emerging and promising research direction. However, centralized paradigms face growing pressure from privacy c…
Personalized Recommendation Models in Federated Settings: A Survey
Chunxu Zhang, Guodong Long, Zijian Zhang +4
Federated recommender systems (FedRecSys) have emerged as a pivotal solution for privacy-aware recommendations, balancing growing demands for data security and personalized experie…