Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks

Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks

5 February 2024

Jian Liang

Papers citing "Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks"

7 / 7 papers shown

Title
FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning Zhihao Zeng Ziquan Fang Wei Shao Lu Chen Yunjun Gao FedML 51 0 0 08 May 2025
Effective and Efficient Cross-City Traffic Knowledge Transfer: A Privacy-Preserving Perspective Zhihao Zeng Ziquan Fang Yuting Huang Lu Chen Yunjun Gao 60 0 0 15 Mar 2025
BlindFL: Segmented Federated Learning with Fully Homomorphic Encryption Evan Gronberg L. dÁliberti Magnus Saebo Aurora Hook FedML 46 0 0 20 Jan 2025
Not all Minorities are Equal: Empty-Class-Aware Distillation for Heterogeneous Federated Learning Kuangpu Guo Yuhe Ding Jian Liang Ran He Zilei Wang Tieniu Tan FedML 37 1 0 04 Jan 2024
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning Yujun Shi Jian Liang Wenqing Zhang Vincent Y. F. Tan Song Bai FedML 79 55 0 01 Oct 2022
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,198 0 01 Sep 2014