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Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

38 / 2,788 papers shown

Title
Attacking Automatic Video Analysis Algorithms: A Case Study of Google Cloud Video Intelligence API Hossein Hosseini Baicen Xiao Andrew Clark Radha Poovendran AAML 72 24 0 14 Aug 2017
Per-instance Differential Privacy Yu Wang 141 5 0 24 Jul 2017
Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking Mostafa Dehghani H. Azarbonyad J. Kamps Maarten de Rijke FedML 51 9 0 24 Jul 2017
Composition Properties of Inferential Privacy for Time-Series Data Shuang Song Kamalika Chaudhuri 51 14 0 10 Jul 2017
Stochastic, Distributed and Federated Optimization for Machine Learning Jakub Konecný FedML 83 38 0 04 Jul 2017
Preserving Differential Privacy in Convolutional Deep Belief Networks Nhathai Phan Xintao Wu Dejing Dou 57 82 0 25 Jun 2017
Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models G. Bernstein Ryan McKenna Tao Sun Daniel Sheldon Michael Hay G. Miklau FedML 102 26 0 14 Jun 2017
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs Cristóbal Esteban Stephanie L. Hyland Gunnar Rätsch GAN SyDa MedIm 148 802 0 08 Jun 2017
Pain-Free Random Differential Privacy with Sensitivity Sampling Benjamin I. P. Rubinstein Francesco Aldà 49 42 0 08 Jun 2017
DeepSecure: Scalable Provably-Secure Deep Learning B. Rouhani M. Riazi F. Koushanfar FedML 91 415 0 24 May 2017
Continual Learning in Generative Adversarial Nets Ari Seff Alex Beatson Daniel Suo Han Liu GAN 92 133 0 23 May 2017
Learning to Succeed while Teaching to Fail: Privacy in Closed Machine Learning Systems Jure Sokolić Qiang Qiu M. Rodrigues Guillermo Sapiro FedML 39 5 0 23 May 2017
LOGAN: Membership Inference Attacks Against Generative Models Jamie Hayes Luca Melis G. Danezis Emiliano De Cristofaro 126 104 0 22 May 2017
Privacy-Preserving Visual Learning Using Doubly Permuted Homomorphic Encryption Ryo Yonetani Vishnu Boddeti Kris Kitani Yoichi Sato PICV FedML 103 67 0 07 Apr 2017
Private Learning on Networks: Part II Shripad Gade Nitin H. Vaidya 168 11 0 27 Mar 2017
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics Seyed Ali Osia Ali Shahin Shamsabadi Sina Sajadmanesh A. Taheri Kleomenis Katevas Hamid R. Rabiee Nicholas D. Lane Hamed Haddadi 107 237 0 08 Mar 2017
Differentially Private Bayesian Learning on Distributed Data Mikko A. Heikkilä Eemil Lagerspetz Samuel Kaski Kana Shimizu Sasu Tarkoma Antti Honkela FedML 182 59 0 03 Mar 2017
Privacy-Preserving Personal Model Training S. S. Rodríguez Liang Wang Jianxin R. Zhao Richard Mortier Hamed Haddadi 70 23 0 01 Mar 2017
Renyi Differential Privacy Ilya Mironov 116 1,271 0 24 Feb 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning Briland Hitaj G. Ateniese Fernando Perez-Cruz FedML 209 1,417 0 24 Feb 2017
DEEProtect: Enabling Inference-based Access Control on Mobile Sensing Applications Changchang Liu Supriyo Chakraborty Prateek Mittal AAML 69 26 0 20 Feb 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 383 1,553 0 25 Jan 2017
Differentially Private Neighborhood-based Recommender Systems Jun Wang Qiang Tang 35 11 0 09 Jan 2017
Simple Black-Box Adversarial Perturbations for Deep Networks Nina Narodytska S. Kasiviswanathan AAML 108 240 0 19 Dec 2016
Private Learning on Networks Shripad Gade Nitin H. Vaidya FedML 36 15 0 15 Dec 2016
Practical Secure Aggregation for Federated Learning on User-Held Data Keith Bonawitz Vladimir Ivanov Ben Kreuter Antonio Marcedone H. B. McMahan Sarvar Patel Daniel Ramage Aaron Segal Karn Seth FedML 98 509 0 14 Nov 2016
Towards the Science of Security and Privacy in Machine Learning Nicolas Papernot Patrick McDaniel Arunesh Sinha Michael P. Wellman AAML 111 474 0 11 Nov 2016
Variational Bayes In Private Settings (VIPS) Mijung Park James R. Foulds Kamalika Chaudhuri Max Welling 129 42 0 01 Nov 2016
Differentially Private Variational Inference for Non-conjugate Models Hibiki Ito O. Dikmen Antti Honkela FedML 97 48 0 27 Oct 2016
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 370 4,182 0 18 Oct 2016
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data Nicolas Papernot Martín Abadi Ulfar Erlingsson Ian Goodfellow Kunal Talwar 222 1,028 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 217 1,917 0 08 Oct 2016
Distributed Optimization for Client-Server Architecture with Negative Gradient Weights Shripad Gade Nitin H. Vaidya 64 4 0 12 Aug 2016
Concrete Problems in AI Safety Dario Amodei C. Olah Jacob Steinhardt Paul Christiano John Schulman Dandelion Mané 442 2,441 0 21 Jun 2016
Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics Xi Wu Fengan Li Arun Kumar Kamalika Chaudhuri S. Jha Jeffrey F. Naughton 76 20 0 15 Jun 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 690 18,071 0 17 Feb 2016
Technical Privacy Metrics: a Systematic Survey Isabel Wagner D. Eckhoff 125 174 0 01 Dec 2015
Learning Privately with Labeled and Unlabeled Examples A. Beimel Kobbi Nissim Uri Stemmer 131 23 0 10 Jul 2014