31 citations · 76 across the 16 of their papers we have counts for
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cs.LG2024
Extracting Spatiotemporal Data from Gradients with Large Language Models
Lele Zheng, Yang Cao, Renhe Jiang +4
Recent works show that sensitive user data can be reconstructed from gradient updates, breaking the key privacy promise of federated learning. While success was demonstrated primar…
cs.CR2024★ 2 cited
Enhancing Privacy of Spatiotemporal Federated Learning against Gradient Inversion Attacks
Lele Zheng, Yang Cao, Renhe Jiang +4
Spatiotemporal federated learning has recently raised intensive studies due to its ability to train valuable models with only shared gradients in various location-based services. O…
cs.CR2024
Federated Graph Analytics with Differential Privacy
Shang Liu, Yang Cao, Takao Murakami +5
Collaborative graph analysis across multiple institutions is becoming increasingly popular. Realistic examples include social network analysis across various social platforms, fina…