1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CR2024★ 1 cited
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…
cs.LG2024
On the Maximal Local Disparity of Fairness-Aware Classifiers
Jinqiu Jin, Haoxuan Li, Fuli Feng
Fairness has become a crucial aspect in the development of trustworthy machine learning algorithms. Current fairness metrics to measure the violation of demographic parity have the…
cs.IR2024
CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation
Jun Wang, Haoxuan Li, Chi Zhang +4
Recommender systems are designed to learn user preferences from observed feedback and comprise many fundamental tasks, such as rating prediction and post-click conversion rate (pCV…