3 citations · 8 across the 5 of their papers we have counts for
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cs.LG2023
Cross-Silo Prototypical Calibration for Federated Learning with Non-IID Data
Zhuang Qi, Lei Meng, Zitan Chen +3
Federated Learning aims to learn a global model on the server side that generalizes to all clients in a privacy-preserving manner, by leveraging the local models from different cli…
cs.IR2023★ 1 cited
Cross-Modal Content Inference and Feature Enrichment for Cold-Start Recommendation
Haokai Ma, Zhuang Qi, Xinxin Dong +3
Multimedia recommendation aims to fuse the multi-modal information of items for feature enrichment to improve the recommendation performance. However, existing methods typically in…
cs.IR2023★ 3 cited
Triple Sequence Learning for Cross-domain Recommendation
Haokai Ma, Ruobing Xie, Lei Meng +4
Cross-domain recommendation (CDR) aims to leverage the correlation of users' behaviors in both the source and target domains to improve the user preference modeling in the target d…