Guoxian Yu

Partial Multi-label Learning with Label and Feature Collaboration

2020 · arXiv (Cornell University)

Partial multi-label learning (PML) models the scenario where each training instance is annotated with a set of candidate labels, and only some of the labels are relevant. The PML problem is practical in real-world scenarios, …

Interaction Privacy Vulnerability in Federated Recommendation and Lossless Countermeasure

2025 · ACM Transactions on Information Systems

Federated Recommendation (FedRec) systems are recognized as privacy-preserving solutions for collaboratively training recommender models without sharing users’ private data. However, recent studies have revealed that FedRec systems are vulnerable to interaction-level membership inference attacks. In …