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Quantifying and Localizing Usable Information Leakage from Neural
  Network Gradients

Quantifying and Localizing Usable Information Leakage from Neural Network Gradients

28 May 2021
Fan Mo
Anastasia Borovykh
Mohammad Malekzadeh
Soteris Demetriou
Deniz Gündüz
Hamed Haddadi
    FedML
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Papers citing "Quantifying and Localizing Usable Information Leakage from Neural Network Gradients"

3 / 3 papers shown
Title
The Future of Digital Health with Federated Learning
The Future of Digital Health with Federated Learning
Nicola Rieke
Jonny Hancox
Wenqi Li
Fausto Milletari
H. Roth
...
Ronald M. Summers
Andrew Trask
Daguang Xu
Maximilian Baust
M. Jorge Cardoso
OOD
174
1,703
0
18 Mar 2020
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
177
1,185
0
30 Nov 2014
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification
Yoon Kim
AILaw
VLM
250
13,360
0
25 Aug 2014
1