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Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 2,788 papers shown

Title
dpUGC: Learn Differentially Private Representation for User Generated Contents Xuan-Son Vu Son N. Tran Lili Jiang 57 14 0 25 Mar 2019
Scalable Differential Privacy with Certified Robustness in Adversarial Learning Nhathai Phan My T. Thai Han Hu R. Jin Tong Sun Dejing Dou 122 14 0 23 Mar 2019
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices Santosh Vempala Andre Wibisono 171 277 0 20 Mar 2019
Privacy Preserving Image-Based Localization Pablo Speciale Johannes L. Schonberger S. B. Kang Sudipta N. Sinha Marc Pollefeys 3DPC 69 84 0 13 Mar 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 116 1,372 0 07 Mar 2019
AutoGAN-based Dimension Reduction for Privacy Preservation Hung Nguyen Di Zhuang Pei-Yuan Wu Jerome Chang 64 33 0 27 Feb 2019
Evaluating Differentially Private Machine Learning in Practice Bargav Jayaraman David Evans 166 7 0 24 Feb 2019
Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment Ziqi Yang E. Chang Zhenkai Liang MLAU 97 60 0 22 Feb 2019
Data collaboration analysis for distributed datasets A. Imakura Tetsuya Sakurai FedML 24 3 0 20 Feb 2019
Differentially Private Continual Learning Sebastian Farquhar Y. Gal FedML MU 58 12 0 18 Feb 2019
Robustness of Neural Networks: A Probabilistic and Practical Approach Ravi Mangal A. Nori A. Orso AAML OOD 78 76 0 15 Feb 2019
Federated Machine Learning: Concept and Applications Qiang Yang Yang Liu Tianjian Chen Yongxin Tong FedML 111 2,372 0 13 Feb 2019
On Lightweight Privacy-Preserving Collaborative Learning for IoT Objects Linshan Jiang Rui Tan Xin Lou Guosheng Lin 67 46 0 13 Feb 2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy T. Tony Cai Yichen Wang Linjun Zhang 160 170 0 12 Feb 2019
Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets D. Froelicher J. Troncoso-Pastoriza João Sá Sousa Jean-Pierre Hubaux OOD SyDa 112 51 0 11 Feb 2019
Achieving Data Utility-Privacy Tradeoff in Internet of Medical Things: A Machine Learning Approach Zhitao Guan Zefang Lv Xiaojiang Du Longfei Wu Mohsen Guizani 35 67 0 08 Feb 2019
Disguised-Nets: Image Disguising for Privacy-preserving Outsourced Deep Learning Sagar Sharma Keke Chen 29 1 0 05 Feb 2019
PUTWorkbench: Analysing Privacy in AI-intensive Systems S. Srivastava Vinay P. Namboodiri T. Prabhakar 41 1 0 05 Feb 2019
CodedPrivateML: A Fast and Privacy-Preserving Framework for Distributed Machine Learning Jinhyun So Başak Güler A. Avestimehr FedML 111 116 0 02 Feb 2019
Privacy Preserving Off-Policy Evaluation Tengyang Xie Philip S. Thomas G. Miklau OffRL 55 4 0 01 Feb 2019
Privacy-preserving Q-Learning with Functional Noise in Continuous State Spaces Baoxiang Wang N. Hegde 114 65 0 30 Jan 2019
Differentially Private Markov Chain Monte Carlo Mikko A. Heikkilä Hibiki Ito O. Dikmen Antti Honkela 80 26 0 29 Jan 2019
Representation Transfer for Differentially Private Drug Sensitivity Prediction Teppo Niinimaki Mikko A. Heikkilä Antti Honkela Samuel Kaski OOD 31 8 0 29 Jan 2019
Bayesian Differential Privacy for Machine Learning Aleksei Triastcyn Boi Faltings 117 2 0 28 Jan 2019
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning Chao Qu Shie Mannor Huan Xu Yuan Qi Le Song Junwu Xiong 100 44 0 27 Jan 2019
SecureBoost: A Lossless Federated Learning Framework Kewei Cheng Tao Fan Yilun Jin Yang Liu Tianjian Chen Dimitrios Papadopoulos Qiang Yang FedML 153 589 0 25 Jan 2019
Better accuracy with quantified privacy: representations learned via reconstructive adversarial network Sicong Liu Anshumali Shrivastava Junzhao Du Lin Zhong 73 13 0 25 Jan 2019
Federated Deep Reinforcement Learning H. Zhuo Wenfeng Feng Yufeng Lin Qian Xu Qiang Yang FedML OffRL 106 90 0 24 Jan 2019
Taming Distrust in the Decentralized Internet with PIXIU Yubin Xia Qingyuan Liu Cheng Tan J. Leng Shangning Xu B. Zang Haibo Chen MoE 57 1 0 18 Jan 2019
LEP-CNN: A Lightweight Edge Device Assisted Privacy-preserving CNN Inference Solution for IoT Yifan Tian Jiawei Yuan Shucheng Yu Yantian Hou 45 9 0 14 Jan 2019
Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data Lorenzo Frigerio Anderson Santana de Oliveira L. Gomez Patrick Duverger SyDa AI4TS 103 109 0 08 Jan 2019
Contamination Attacks and Mitigation in Multi-Party Machine Learning Jamie Hayes O. Ohrimenko AAML FedML 119 75 0 08 Jan 2019
Application-driven Privacy-preserving Data Publishing with Correlated Attributes A. Rezaei Chaowei Xiao Jie Gao Yue Liu Sirajum Munir 60 14 0 26 Dec 2018
Privacy-Preserving Collaborative Deep Learning with Unreliable Participants Lingchen Zhao Qian Wang Qin Zou Yan Zhang Yanjiao Chen FedML 45 9 0 25 Dec 2018
Multi-objective Evolutionary Federated Learning Hangyu Zhu Yaochu Jin FedML 91 240 0 18 Dec 2018
A General Approach to Adding Differential Privacy to Iterative Training Procedures H. B. McMahan Galen Andrew Ulfar Erlingsson Steve Chien Ilya Mironov Nicolas Papernot Peter Kairouz 126 193 0 15 Dec 2018
Construction of Differentially Private Empirical Distributions from a low-order Marginals Set through Solving Linear Equations with l2 Regularization E. Eugenio Fang Liu 25 3 0 12 Dec 2018
No Peek: A Survey of private distributed deep learning Praneeth Vepakomma Tristan Swedish Ramesh Raskar O. Gupta Abhimanyu Dubey SyDa FedML 86 100 0 08 Dec 2018
Reaching Data Confidentiality and Model Accountability on the CalTrain Zhongshu Gu Hani Jamjoom D. Su Heqing Huang Jialong Zhang Tengfei Ma Dimitrios E. Pendarakis Ian Molloy FedML 73 16 0 07 Dec 2018
A Hybrid Approach to Privacy-Preserving Federated Learning Stacey Truex Nathalie Baracaldo Ali Anwar Thomas Steinke Heiko Ludwig Rui Zhang Yi Zhou FedML 104 909 0 07 Dec 2018
Applied Federated Learning: Improving Google Keyboard Query Suggestions Timothy Yang Galen Andrew Hubert Eichner Haicheng Sun Wei Li Nicholas Kong Daniel Ramage F. Beaufays FedML 114 626 0 07 Dec 2018
Three Tools for Practical Differential Privacy K. V. D. Veen Ruben Seggers Peter Bloem Giorgio Patrini 70 39 0 07 Dec 2018
Privacy Partitioning: Protecting User Data During the Deep Learning Inference Phase Jianfeng Chi Emmanuel Owusu Xuwang Yin Tong Yu William Chan P. Tague Yuan Tian FedML 71 28 0 07 Dec 2018
When Homomorphic Cryptosystem Meets Differential Privacy: Training Machine Learning Classifier with Privacy Protection Xiangyun Tang Liehuang Zhu Meng Shen Xiaojiang Du 19 4 0 06 Dec 2018
Differentially Private Data Generative Models Qingrong Chen Chong Xiang Minhui Xue Yue Liu Nikita Borisov Dali Kaafar Haojin Zhu SyDa AAML 96 79 0 06 Dec 2018
Privacy-Preserving Distributed Deep Learning for Clinical Data Brett K. Beaulieu-Jones W. Yuan S. G. Finlayson Zhiwei Steven Wu OOD FedML 68 46 0 04 Dec 2018
Protection Against Reconstruction and Its Applications in Private Federated Learning Abhishek Bhowmick John C. Duchi Julien Freudiger Gaurav Kapoor Ryan M. Rogers FedML 130 362 0 03 Dec 2018
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV AAML 78 251 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 138 723 0 03 Dec 2018
Deep Learning Application in Security and Privacy -- Theory and Practice: A Position Paper Julia A. Meister Raja Naeem Akram K. Markantonakis 51 0 0 01 Dec 2018