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Meiting Xue

2 accepted papers

2026

Class-Aware Active Annotation in Federated Semi-Supervised Learning for Medical Image Classification

AAAI 2026technical

In medical image classification, data privacy constraints and the high cost of expert annotations pose significant challenges to building generalizable models. Federated semi-supervised learning (FSSL), which combines the privacy-preserving nature of federated learning with the label efficiency of s

Cited by 0SourcePDFScholar
2025

FedCCH: Automatic Personalized Graph Federated Learning for Inter-Client and Intra-Client Heterogeneity

IJCAI 2025

Graph federated learning (GFL) is increasingly utilized in domains such as social network analysis and recommendation systems, where non-IID data exist extensively and necessitate a strong emphasis on personalized learning. However, existing methods focus only on the personality among different clie

Cited by 0SourcePDFScholar