Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification

19 November 2021

Papers citing "Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification"

7 / 7 papers shown

Title
R-GAP: Recursive Gradient Attack on Privacy Junyi Zhu Matthew Blaschko FedML 54 137 0 15 Oct 2020
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks Lixin Fan Kam Woh Ng Ce Ju Tianyu Zhang Chang Liu Chee Seng Chan Qiang Yang MIACV 33 64 0 20 Jun 2020
iDLG: Improved Deep Leakage from Gradients Bo Zhao Konda Reddy Mopuri Hakan Bilen FedML 81 643 0 08 Jan 2020
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 103 2,227 0 21 Jun 2019
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 408 17,615 0 17 Feb 2016
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 254 4,681 0 21 Dec 2014
scikit-image: Image processing in Python Stéfan van der Walt Johannes L. Schonberger Juan Nunez-Iglesias François Boulogne Joshua D. Warner Neil Yager Emmanuelle Gouillart Tony Yu the scikit-image contributors SSeg GP VLM 198 4,351 0 23 Jul 2014