NoPeek: Information leakage reduction to share activations in distributed deep learning

20 August 2020

Papers citing "NoPeek: Information leakage reduction to share activations in distributed deep learning"

33 / 33 papers shown

Title
Quantifying Privacy Leakage in Split Inference via Fisher-Approximated Shannon Information Analysis Ruijun Deng Zhihui Lu Qiang Duan FedML 104 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 87 2 0 01 Mar 2025
Navigating the Designs of Privacy-Preserving Fine-tuning for Large Language Models Haonan Shi Tu Ouyang An Wang 71 0 0 08 Jan 2025
Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning Wei Yang Bryan Lim Jer Shyuan Ng Zehui Xiong Dusit Niyato Cyril Leung Chunyan Miao Qiang Yang FedML 34 25 0 31 May 2020
SplitFed: When Federated Learning Meets Split Learning Chandra Thapa Pathum Chamikara Mahawaga Arachchige S. Çamtepe Lichao Sun FedML 71 573 0 25 Apr 2020
On the Global Optima of Kernelized Adversarial Representation Learning Bashir Sadeghi Runyi Yu Vishnu Boddeti AAML 69 31 0 16 Oct 2019
Detailed comparison of communication efficiency of split learning and federated learning Abhishek Singh Praneeth Vepakomma O. Gupta Ramesh Raskar FedML 43 188 0 18 Sep 2019
Data-Efficient Mutual Information Neural Estimator Xiaoyu Lin Indranil Sur Samuel A. Nastase Ajay Divakaran Uri Hasson Mohamed R. Amer DRL 50 20 0 08 May 2019
FlowSAN: Privacy-enhancing Semi-Adversarial Networks to Confound Arbitrary Face-based Gender Classifiers Vahid Mirjalili S. Raschka Arun Ross PICV CVBM 20 47 0 03 May 2019
Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach P. Roy Vishnu Boddeti 13 99 0 11 Apr 2019
Protection Against Reconstruction and Its Applications in Private Federated Learning Abhishek Bhowmick John C. Duchi Julien Freudiger Gaurav Kapoor Ryan M. Rogers FedML 45 358 0 03 Dec 2018
Split learning for health: Distributed deep learning without sharing raw patient data Praneeth Vepakomma O. Gupta Tristan Swedish Ramesh Raskar FedML 83 694 0 03 Dec 2018
A fast algorithm for computing distance correlation A. Chaudhuri Wenhao Hu 61 65 0 26 Oct 2018
Distributed learning of deep neural network over multiple agents O. Gupta Ramesh Raskar FedML OOD 44 602 0 14 Oct 2018
Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study Zhenyu Wu Zhangyang Wang Zhaowen Wang Hailin Jin AAML PICV 53 153 0 22 Jul 2018
Secure Face Matching Using Fully Homomorphic Encryption Vishnu Boddeti PICV CVBM 85 109 0 01 May 2018
Mitigating Unwanted Biases with Adversarial Learning B. Zhang Blake Lemoine Margaret Mitchell FaML 106 1,373 0 22 Jan 2018
Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs using Deep Learning Ryan Poplin A. Varadarajan Katy Blumer Yun-Hui Liu M. McConnell G. Corrado L. Peng D. Webster MedIm 46 1,326 0 31 Aug 2017
Privacy-Preserving Visual Learning Using Doubly Permuted Homomorphic Encryption Ryo Yonetani Vishnu Boddeti Kris Kitani Yoichi Sato PICV FedML 56 67 0 07 Apr 2017
Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images Rakshith Shetty Bernt Schiele Mario Fritz 75 226 0 30 Mar 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 107 1,385 0 24 Feb 2017
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data Nicolas Papernot Martín Abadi Ulfar Erlingsson Ian Goodfellow Kunal Talwar 50 1,009 0 18 Oct 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 267 4,620 0 18 Oct 2016
Supervised Dimensionality Reduction via Distance Correlation Maximization Praneeth Vepakomma Chetan Tonde Ahmed Elgammal 48 38 0 03 Jan 2016
Censoring Representations with an Adversary Harrison Edwards Amos Storkey AAML FaML 47 504 0 18 Nov 2015
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 149 633 0 03 Nov 2015
Fast Computing for Distance Covariance X. Huo G. Székely 68 128 0 06 Oct 2014
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 129 317 0 18 Feb 2014
Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization Julien Mairal 76 160 0 19 Jun 2013
The affinely invariant distance correlation J. Dueck Dominic Edelmann T. Gneiting Donald Richards 122 42 0 09 Oct 2012
Equivalence of distance-based and RKHS-based statistics in hypothesis testing Dino Sejdinovic Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu 134 681 0 25 Jul 2012
Hypothesis testing using pairwise distances and associated kernels (with Appendix) Dino Sejdinovic Arthur Gretton Bharath K. Sriperumbudur Kenji Fukumizu 86 39 0 02 May 2012
Measuring and testing dependence by correlation of distances G. Székely Maria L. Rizzo N. K. Bakirov 221 2,586 0 28 Mar 2008