v1v2 (latest)

Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 2,789 papers shown

Title
Differentially private sub-Gaussian location estimators Marco Avella-Medina Victor-Emmanuel Brunel 74 18 0 27 Jun 2019
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference Klas Leino Matt Fredrikson MIACV 135 280 0 27 Jun 2019
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks Tribhuvanesh Orekondy Bernt Schiele Mario Fritz AAML 100 167 0 26 Jun 2019
The Value of Collaboration in Convex Machine Learning with Differential Privacy Nan Wu Farhad Farokhi David B. Smith M. Kâafar FedML 87 100 0 24 Jun 2019
Secure Multi-party Computation for Cloud-based Control A. Alexandru George J. Pappas 65 27 0 23 Jun 2019
The Cost of a Reductions Approach to Private Fair Optimization Daniel Alabi 96 3 0 23 Jun 2019
G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators Yunhui Long Wei Ping Zhuolin Yang B. Kailkhura Aston Zhang C.A. Gunter Yue Liu 128 75 0 21 Jun 2019
Reversible Privacy Preservation using Multi-level Encryption and Compressive Sensing Mehmet Yamaç Mete Ahishali Nikolaos Passalis Jenni Raitoharju B. Sankur Moncef Gabbouj PICV 48 20 0 20 Jun 2019
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model Badih Ghazi Rasmus Pagh A. Velingker FedML 105 99 0 19 Jun 2019
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation Han Zhao Jianfeng Chi Yuan Tian Geoffrey J. Gordon MIACV 73 2 0 19 Jun 2019
Membership Privacy for Machine Learning Models Through Knowledge Transfer Virat Shejwalkar Amir Houmansadr 100 10 0 15 Jun 2019
Effectiveness of Distillation Attack and Countermeasure on Neural Network Watermarking Ziqi Yang Hung Dang E. Chang AAML 129 34 0 14 Jun 2019
Does Learning Require Memorization? A Short Tale about a Long Tail Vitaly Feldman TDI 249 518 0 12 Jun 2019
Federated Learning for Emoji Prediction in a Mobile Keyboard Swaroop Indra Ramaswamy Rajiv Mathews Kanishka Rao Franccoise Beaufays FedML 90 314 0 11 Jun 2019
Computing Tight Differential Privacy Guarantees Using FFT A. Koskela Hibiki Ito Antti Honkela 22 1 0 07 Jun 2019
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation Mark Bun Thomas Steinke 89 76 0 06 Jun 2019
Private Deep Learning with Teacher Ensembles Lichao Sun Yingbo Zhou Ji Wang Jia Li R. Socher Philip S. Yu Caiming Xiong FedML 34 2 0 05 Jun 2019
Interpretable and Differentially Private Predictions Frederik Harder Matthias Bauer Mijung Park FAtt 98 54 0 05 Jun 2019
Locally Differentially Private Data Collection and Analysis Teng Wang Jun Zhao Xinyu Yang Xuebin Ren 71 13 0 05 Jun 2019
Privacy-preserving Crowd-guided AI Decision-making in Ethical Dilemmas Teng Wang Jun Zhao Han Yu Jinyan Liu Xinyu Yang Xuebin Ren Shuyu Shi 82 11 0 04 Jun 2019
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 176 130 0 04 Jun 2019
On Privacy Protection of Latent Dirichlet Allocation Model Training Fangyuan Zhao Xuebin Ren Shusen Yang Xinyu Yang 71 5 0 04 Jun 2019
Towards Fair and Privacy-Preserving Federated Deep Models Lingjuan Lyu Jiangshan Yu Karthik Nandakumar Yitong Li Xingjun Ma Jiong Jin Han Yu Kee Siong Ng FedML 52 20 0 04 Jun 2019
Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness Nhathai Phan Minh Nhat Vu Yang Liu R. Jin Dejing Dou Xintao Wu My T. Thai AAML 69 52 0 02 Jun 2019
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification Bingzhe Wu Shiwan Zhao Guangyu Sun Xiaolu Zhang Zhong Su C. Zeng Zhihong Liu 82 41 0 30 May 2019
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models Amrita Roy Chowdhury Theodoros Rekatsinas S. Jha 56 11 0 30 May 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 187 489 0 28 May 2019
Shredder: Learning Noise Distributions to Protect Inference Privacy Fatemehsadat Mireshghallah Mohammadkazem Taram Prakash Ramrakhyani Dean Tullsen H. Esmaeilzadeh 91 11 0 26 May 2019
Automatic Discovery of Privacy-Utility Pareto Fronts Brendan Avent Javier I. González Tom Diethe Andrei Paleyes Borja Balle FedML 96 29 0 26 May 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 111 252 0 24 May 2019
Hypothesis Testing Interpretations and Renyi Differential Privacy Borja Balle Gilles Barthe Marco Gaboardi Justin Hsu Tetsuya Sato 111 120 0 24 May 2019
Knowledge Transferring via Model Aggregation for Online Social Care Shaoxiong Ji Guodong Long Shirui Pan Tianqing Zhu Jing Jiang Sen Wang Xue Li 51 0 0 19 May 2019
Towards Automatic Generation of Shareable Synthetic Clinical Notes Using Neural Language Models Oren Melamud Chaitanya P. Shivade SyDa MedIm 85 37 0 16 May 2019
Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms K. S. S. Kumar M. Deisenroth 82 6 0 13 May 2019
Differentially Private Learning with Adaptive Clipping Galen Andrew Om Thakkar H. B. McMahan Swaroop Ramaswamy FedML 127 349 0 09 May 2019
MixMatch: A Holistic Approach to Semi-Supervised Learning David Berthelot Nicholas Carlini Ian Goodfellow Nicolas Papernot Avital Oliver Colin Raffel 275 3,068 0 06 May 2019
Genuinely Distributed Byzantine Machine Learning El-Mahdi El-Mhamdi R. Guerraoui Arsany Guirguis Lê Nguyên Hoang Sébastien Rouault FedML OOD 85 19 0 05 May 2019
Free Gap Information from the Differentially Private Sparse Vector and Noisy Max Mechanisms Zeyu Ding Yuxin Wang Qiang Yan Daniel Kifer 101 14 0 29 Apr 2019
How You Act Tells a Lot: Privacy-Leakage Attack on Deep Reinforcement Learning Xinlei Pan Weiyao Wang Xiaoshuai Zhang Yue Liu Jinfeng Yi Basel Alomair MIACV 151 26 0 24 Apr 2019
Distributed Differentially Private Computation of Functions with Correlated Noise H. Imtiaz Jafar Mohammadi Anand D. Sarwate OOD 78 10 0 22 Apr 2019
HARK Side of Deep Learning -- From Grad Student Descent to Automated Machine Learning O. Gencoglu M. Gils E. Guldogan Chamin Morikawa Mehmet Süzen M. Gruber J. Leinonen H. Huttunen 113 38 0 16 Apr 2019
CryptoNN: Training Neural Networks over Encrypted Data Runhua Xu J. Joshi Chong Li 84 77 0 15 Apr 2019
Differential Privacy for Eye-Tracking Data Ao Liu Lirong Xia A. Duchowski Reynold J. Bailey K. Holmqvist Eakta Jain 79 74 0 15 Apr 2019
Distributed Layer-Partitioned Training for Privacy-Preserved Deep Learning Chun-Hsien Yu Chun-Nan Chou Emily Chang FedML 44 13 0 12 Apr 2019
What Storage Access Privacy is Achievable with Small Overhead? Sarvar Patel G. Persiano Kevin Yeo 47 16 0 10 Apr 2019
Generative Models for Novelty Detection: Applications in abnormal event and situational change detection from data series Mahdyar Ravanbakhsh 42 1 0 09 Apr 2019
Private Hierarchical Clustering and Efficient Approximation Xianrui Meng D. Papadopoulos Alina Oprea Nikos Triandopoulos FedML 83 0 0 09 Apr 2019
Differentially Private Model Publishing for Deep Learning Lei Yu Ling Liu C. Pu Mehmet Emre Gursoy Stacey Truex FedML 146 270 0 03 Apr 2019
Maximal Information Leakage based Privacy Preserving Data Disclosure Mechanisms Tianrui Xiao Ashish Khisti 59 5 0 01 Apr 2019
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning A. Salem Apratim Bhattacharyya Michael Backes Mario Fritz Yang Zhang FedML AAML MIACV 124 262 0 01 Apr 2019