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2003.12365
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Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?
16 March 2020
Sharif Abuadbba
Kyuyeon Kim
Minki Kim
Chandra Thapa
S. Çamtepe
Yansong Gao
Hyoungshick Kim
Surya Nepal
FedML
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Papers citing
"Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?"
8 / 8 papers shown
Title
Quantifying Privacy Leakage in Split Inference via Fisher-Approximated Shannon Information Analysis
Ruijun Deng
Zhihui Lu
Qiang Duan
FedML
81
0
0
14 Apr 2025
Theoretical Insights in Model Inversion Robustness and Conditional Entropy Maximization for Collaborative Inference Systems
Song Xia
Yi Yu
Wenhan Yang
Meiwen Ding
Zhuo Chen
Lingyu Duan
Alex C. Kot
Xudong Jiang
85
2
0
01 Mar 2025
Can You Really Backdoor Federated Learning?
Ziteng Sun
Peter Kairouz
A. Suresh
H. B. McMahan
FedML
48
565
0
18 Nov 2019
Split learning for health: Distributed deep learning without sharing raw patient data
Praneeth Vepakomma
O. Gupta
Tristan Swedish
Ramesh Raskar
FedML
78
694
0
03 Dec 2018
Distributed learning of deep neural network over multiple agents
O. Gupta
Ramesh Raskar
FedML
OOD
42
602
0
14 Oct 2018
Exploiting Unintended Feature Leakage in Collaborative Learning
Luca Melis
Congzheng Song
Emiliano De Cristofaro
Vitaly Shmatikov
FedML
111
1,461
0
10 May 2018
Federated Learning: Strategies for Improving Communication Efficiency
Jakub Konecný
H. B. McMahan
Felix X. Yu
Peter Richtárik
A. Suresh
Dave Bacon
FedML
249
4,620
0
18 Oct 2016
Deep Learning in Neural Networks: An Overview
Jürgen Schmidhuber
HAI
132
16,311
0
30 Apr 2014
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