Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks

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Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks

International Conference on Learning Representations (ICLR), 2024

5 February 2024

Jian Liang

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

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MAGIA: Sensing Per-Image Signals from Single-Round Averaged Gradients for Label-Inference-Free Gradient Inversion Zhanting Zhou Jinbo Wang Zeqin Wu Fengli Zhang 96 0 0 17 Sep 2025
A Comprehensive Survey on Trustworthiness in Reasoning with Large Language Models Yanbo Wang Yongcan Yu Jian Liang Ran He HILM LRM 197 4 0 04 Sep 2025
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 234 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 523 0 0 15 Mar 2025
BlindFL: Segmented Federated Learning with Fully Homomorphic Encryption Evan Gronberg L. dÁliberti Magnus Saebo Aurora Hook FedML 196 0 0 20 Jan 2025