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20232026
most citedFedFDP: Fairness-Aware Federated Learning with Differential Privacy

1 citations · 3 across the 8 of their papers we have counts for

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2 papers · 1 filter

cs.LG2025

scAGC: Learning Adaptive Cell Graphs with Contrastive Guidance for Single-Cell Clustering

Huifa Li, Jie Fu, Xinlin Zhuang +6

Accurate cell type annotation is a crucial step in analyzing single-cell RNA sequencing (scRNA-seq) data, which provides valuable insights into cellular heterogeneity. However, due…

cs.LG2025

EC-LDA : Label Distribution Inference Attack against Federated Graph Learning with Embedding Compression

Tong Cheng, Jie Fu, Xinpeng Ling +4

Graph Neural Networks (GNNs) have been widely used for graph analysis. Federated Graph Learning (FGL) is an emerging learning framework to collaboratively train graph data from var…