Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 1,157 papers shown

Title
Stochastic Adaptive Line Search for Differentially Private Optimization Chen Chen Jaewoo Lee 30 14 0 18 Aug 2020
Siloed Federated Learning for Multi-Centric Histopathology Datasets M. Andreux Jean Ogier du Terrail C. Béguier Eric W. Tramel FedML OOD AI4CE 20 113 0 17 Aug 2020
Fast Dimension Independent Private AdaGrad on Publicly Estimated Subspaces Peter Kairouz Mónica Ribero Keith Rush Abhradeep Thakurta 93 14 0 14 Aug 2020
Synthesizing Property & Casualty Ratemaking Datasets using Generative Adversarial Networks Marie-Pier Côté Brian Hartman Olivier Mercier Joshua Meyers Jared Cummings Elijah Harmon GAN SyDa 33 8 0 13 Aug 2020
Differentially Private Accelerated Optimization Algorithms Nurdan Kuru cS. .Ilker Birbil Mert Gurbuzbalaban S. Yıldırım 38 23 0 05 Aug 2020
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence Tianqing Zhu Dayong Ye Wei Wang Wanlei Zhou Philip S. Yu SyDa 38 125 0 05 Aug 2020
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization Rui Hu Yanmin Gong Yuanxiong Guo FedML 34 55 0 01 Aug 2020
Correlated Data in Differential Privacy: Definition and Analysis Tao Zhang Tianqing Zhu Renping Liu Wanlei Zhou 29 13 0 01 Aug 2020
SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization Jiazhi Xia Tianxiang Chen Lei Zhang Wei Chen Yang Chen X. Zhang C. Xie Tobias Schreck 15 11 0 30 Jul 2020
Membership Leakage in Label-Only Exposures Zheng Li Yang Zhang 34 237 0 30 Jul 2020
Learner's Dilemma: IoT Devices Training Strategies in Collaborative Deep Learning Deepti Gupta O. Kayode Smriti Bhatt Maanak Gupta A. Tosun 21 23 0 30 Jul 2020
VFL: A Verifiable Federated Learning with Privacy-Preserving for Big Data in Industrial IoT Anmin Fu Xianglong Zhang N. Xiong Yansong Gao Huaqun Wang FedML 24 174 0 27 Jul 2020
Anonymizing Machine Learning Models Abigail Goldsteen Gilad Ezov Ron Shmelkin Micha Moffie Ariel Farkash MIACV 19 5 0 26 Jul 2020
Private Post-GAN Boosting Marcel Neunhoeffer Zhiwei Steven Wu Cynthia Dwork 122 29 0 23 Jul 2020
Breaking the Communication-Privacy-Accuracy Trilemma Wei-Ning Chen Peter Kairouz Ayfer Özgür 24 116 0 22 Jul 2020
Privacy-preserving Artificial Intelligence Techniques in Biomedicine Reihaneh Torkzadehmahani Reza Nasirigerdeh David B. Blumenthal T. Kacprowski M. List ... Harald H. H. W. Schmidt A. Schwalber Christof Tschohl Andrea Wohner Jan Baumbach 28 60 0 22 Jul 2020
IBM Federated Learning: an Enterprise Framework White Paper V0.1 Heiko Ludwig Nathalie Baracaldo Gegi Thomas Yi Zhou Ali Anwar ... Sean Laguna Mikhail Yurochkin Mayank Agarwal Ebube Chuba Annie Abay FedML 131 157 0 22 Jul 2020
Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise Marten van Dijk Nhuong V. Nguyen Toan N. Nguyen Lam M. Nguyen Quoc Tran-Dinh Phuong Ha Nguyen FedML 28 28 0 17 Jul 2020
Federated Learning in Mobile Edge Computing: An Edge-Learning Perspective for Beyond 5G Shashank Jere Q. Fan Bodong Shang Lianjun Li Lingjia Liu 27 10 0 15 Jul 2020
A Survey of Privacy Attacks in Machine Learning M. Rigaki Sebastian Garcia PILM AAML 39 213 0 15 Jul 2020
Differentially private cross-silo federated learning Mikko A. Heikkilä A. Koskela Kana Shimizu Samuel Kaski Antti Honkela FedML 29 24 0 10 Jul 2020
The Trade-Offs of Private Prediction Laurens van der Maaten Awni Y. Hannun 25 22 0 09 Jul 2020
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification Yingxue Zhou Zhiwei Steven Wu A. Banerjee 29 108 0 07 Jul 2020
PPaaS: Privacy Preservation as a Service Pathum Chamikara Mahawaga Arachchige P. Bertók I. Khalil Dongxi Liu S. Çamtepe 27 9 0 04 Jul 2020
A Statistical Overview on Data Privacy Fang Liu 19 5 0 01 Jul 2020
Reducing Risk of Model Inversion Using Privacy-Guided Training Abigail Goldsteen Gilad Ezov Ariel Farkash 33 4 0 29 Jun 2020
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds Yingxue Zhou Xiangyi Chen Mingyi Hong Zhiwei Steven Wu A. Banerjee 32 25 0 24 Jun 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 17 63 0 20 Jun 2020
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes Mike Gartrell Insu Han Elvis Dohmatob Jennifer Gillenwater Victor-Emmanuel Brunel 31 16 0 17 Jun 2020
SPEED: Secure, PrivatE, and Efficient Deep learning Arnaud Grivet Sébert Rafael Pinot Martin Zuber Cédric Gouy-Pailler Renaud Sirdey FedML 15 20 0 16 Jun 2020
Model Explanations with Differential Privacy Neel Patel Reza Shokri Yair Zick SILM FedML 28 32 0 16 Jun 2020
Balance is key: Private median splits yield high-utility random trees Shorya Consul Sinead Williamson 25 2 0 15 Jun 2020
Towards practical differentially private causal graph discovery Lun Wang Qi Pang D. Song 31 13 0 15 Jun 2020
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems Sixu Hu Yuan N. Li Xu Liu Yue Liu Zhaomin Wu Bingsheng He FedML 23 54 0 14 Jun 2020
Topology-aware Differential Privacy for Decentralized Image Classification Shangwei Guo Tianwei Zhang Guowen Xu Hanzhou Yu Tao Xiang Yang Liu 27 18 0 14 Jun 2020
FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction Georgios Damaskinos R. Guerraoui Anne-Marie Kermarrec Vlad Nitu Rhicheek Patra Francois Taiani 21 54 0 12 Jun 2020
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses Raef Bassily Vitaly Feldman Cristóbal Guzmán Kunal Talwar MLT 24 192 0 12 Jun 2020
Evading Curse of Dimensionality in Unconstrained Private GLMs via Private Gradient Descent Shuang Song Thomas Steinke Om Thakkar Abhradeep Thakurta 35 50 0 11 Jun 2020
Secure Byzantine-Robust Machine Learning Lie He Sai Praneeth Karimireddy Martin Jaggi OOD 26 58 0 08 Jun 2020
ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing T. Ryffel Pierre Tholoniat D. Pointcheval Francis R. Bach FedML 30 94 0 08 Jun 2020
Privacy Adversarial Network: Representation Learning for Mobile Data Privacy Sicong Liu Junzhao Du Anshumali Shrivastava Lin Zhong 59 14 0 08 Jun 2020
Generation of Differentially Private Heterogeneous Electronic Health Records Kieran Chin-Cheong Thomas M. Sutter Julia E. Vogt SyDa 14 6 0 05 Jun 2020
Federated Learning for 6G Communications: Challenges, Methods, and Future Directions Yi Liu Xingliang Yuan Zehui Xiong Jiawen Kang Xiaofei Wang Dusit Niyato FedML AI4CE 10 279 0 04 Jun 2020
Revisiting Membership Inference Under Realistic Assumptions Bargav Jayaraman Lingxiao Wang Katherine Knipmeyer Quanquan Gu David Evans 24 149 0 21 May 2020
Privacy Preserving Face Recognition Utilizing Differential Privacy Pathum Chamikara Mahawaga Arachchige P. Bertók I. Khalil D. Liu S. Çamtepe PICV 52 118 0 21 May 2020
An Overview of Privacy in Machine Learning Emiliano De Cristofaro SILM 35 83 0 18 May 2020
Near Instance-Optimality in Differential Privacy Hilal Asi John C. Duchi 34 38 0 16 May 2020
Efficient Federated Learning over Multiple Access Channel with Differential Privacy Constraints Amir Sonee Stefano Rini 19 16 0 15 May 2020
Federated Recommendation System via Differential Privacy Tan Li Linqi Song Christina Fragouli FedML 29 60 0 14 May 2020
Private Stochastic Convex Optimization: Optimal Rates in Linear Time Vitaly Feldman Tomer Koren Kunal Talwar 22 204 0 10 May 2020