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Jiahuan Luo

2 accepted papers

2023

FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation

IJCAI 2023poster

Vertical federated learning (VFL) allows an active party with labeled data to leverage auxiliary features from the passive parties to improve model performance. Concerns about the private feature and label leakage in both the training and inference phases of VFL have drawn wide research attention. I…

Cited by 18SourcePDFScholar
2022

FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning

IJCAI 2022poster

Federated learning (FL) aims to protect data privacy by enabling clients to build machine learning models collaboratively without sharing their private data. Recent works demonstrate that information exchanged during FL is subject to gradient-based privacy attacks and, consequently, a variety of pri…

Cited by 90SourcePDFScholar