5 papers
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…
CoDS: Enhancing Collaborative Perception in Heterogeneous Scenarios via Domain Separation
Yushan Han, Hui Zhang, Honglei Zhang +3
Collaborative perception has been proven to improve individual perception in autonomous driving through multi-agent interaction. Nevertheless, most methods often assume identical e…
CoDTS: Enhancing Sparsely Supervised Collaborative Perception with a Dual Teacher-Student Framework
Yushan Han, Hui Zhang, Honglei Zhang +2
Current collaborative perception methods often rely on fully annotated datasets, which can be expensive to obtain in practical situations. To reduce annotation costs, some works ad…
A Tutorial of Personalized Federated Recommender Systems: Recent Advances and Future Directions
Jing Jiang, Chunxu Zhang, Honglei Zhang +3
Personalization stands as the cornerstone of recommender systems (RecSys), striving to sift out redundant information and offer tailor-made services for users. However, the convent…
Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation
Honglei Zhang, Haoxuan Li, Jundong Chen +6
Federated recommendation aims to collect global knowledge by aggregating local models from massive devices, to provide recommendations while ensuring privacy. Current methods mainl…