84 citations · 101 across the 11 of their papers we have counts for
3 papers · 1 filter
MDiffFR: Modality-Guided Diffusion Generation for Cold-start Items in Federated Recommendation
Kang Fu, Honglei Zhang, Xuechao Zou +1
Federated recommendations (FRs) provide personalized services while preserving user privacy by keeping user data on local clients, which has attracted significant attention in rece…
Breaking the Aggregation Bottleneck in Federated Recommendation: A Personalized Model Merging Approach
Jundong Chen, Honglei Zhang, Chunxu Zhang +2
Federated recommendation (FR) facilitates collaborative training by aggregating local models from massive devices, enabling client-specific personalization while ensuring privacy.…
Beyond Personalization: Federated Recommendation with Calibration via Low-rank Decomposition
Jundong Chen, Honglei Zhang, Haoxuan Li +3
Federated recommendation (FR) is a promising paradigm to protect user privacy in recommender systems. Distinct from general federated scenarios, FR inherently needs to preserve cli…