Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 1,131 papers shown

Title
Privacy-Preserving Models for Legal Natural Language Processing Ying Yin Ivan Habernal PILM AILaw 11 8 0 05 Nov 2022
Privacy-preserving Deep Learning based Record Linkage Thilina Ranbaduge Dinusha Vatsalan Ming Ding 27 10 0 03 Nov 2022
Distributed DP-Helmet: Scalable Differentially Private Non-interactive Averaging of Single Layers Moritz Kirschte Sebastian Meiser Saman Ardalan Esfandiar Mohammadi FedML 34 0 0 03 Nov 2022
Revisiting Hyperparameter Tuning with Differential Privacy Youlong Ding Xueyang Wu 24 0 0 03 Nov 2022
Private Semi-supervised Knowledge Transfer for Deep Learning from Noisy Labels Qiuchen Zhang Jing Ma Jian Lou Li Xiong Xiaoqian Jiang NoLa 21 0 0 03 Nov 2022
Privacy-preserving Non-negative Matrix Factorization with Outliers Swapnil Saha H. Imtiaz PICV 21 3 0 02 Nov 2022
Private optimization in the interpolation regime: faster rates and hardness results Hilal Asi Karan N. Chadha Gary Cheng John C. Duchi 49 5 0 31 Oct 2022
Two Models are Better than One: Federated Learning Is Not Private For Google GBoard Next Word Prediction Mohamed Suliman D. Leith SILM FedML 26 7 0 30 Oct 2022
On the Vulnerability of Data Points under Multiple Membership Inference Attacks and Target Models Mauro Conti Jiaxin Li S. Picek MIALM 37 2 0 28 Oct 2022
Differential Privacy has Bounded Impact on Fairness in Classification Paul Mangold Michaël Perrot A. Bellet Marc Tommasi 41 17 0 28 Oct 2022
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 41 2 0 28 Oct 2022
DPVIm: Differentially Private Variational Inference Improved Joonas Jälkö Lukas Prediger Antti Honkela Samuel Kaski 39 3 0 28 Oct 2022
Privately Fine-Tuning Large Language Models with Differential Privacy R. Behnia Mohammadreza Ebrahimi Jason L. Pacheco B. Padmanabhan 37 45 0 26 Oct 2022
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe Xiang Yue Huseyin A. Inan Xuechen Li Girish Kumar Julia McAnallen Hoda Shajari Huan Sun David Levitan Robert Sim 63 79 0 25 Oct 2022
Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano Chuan Guo Alexandre Sablayrolles Maziar Sanjabi FedML 29 17 0 24 Oct 2022
NVIDIA FLARE: Federated Learning from Simulation to Real-World H. Roth Yan Cheng Yuhong Wen Isaac Yang Ziyue Xu ... Daguang Xu Nic Ma Prerna Dogra Mona G. Flores Andrew Feng FedML AI4CE 27 97 0 24 Oct 2022
Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses Adnan Qayyum M. A. Butt Hassan Ali Muhammad Usman O. Halabi Ala I. Al-Fuqaha Q. Abbasi Muhammad Ali Imran Junaid Qadir 35 32 0 24 Oct 2022
Learning to Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning Ruihan Wu Xiangyu Chen Chuan Guo Kilian Q. Weinberger FedML 20 26 0 19 Oct 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Yifan Yang 48 20 0 18 Oct 2022
Review Learning: Alleviating Catastrophic Forgetting with Generative Replay without Generator Jaesung Yoo Sung-Hyuk Choi Yewon Yang Suhyeon Kim J. Choi ... H. J. Joo Dae-Jung Kim R. Park Hyeong-Jin Yoon Kwangsoo Kim KELM OffRL 40 0 0 17 Oct 2022
Forget Unlearning: Towards True Data-Deletion in Machine Learning R. Chourasia Neil Shah MU 21 40 0 17 Oct 2022
A General Framework for Auditing Differentially Private Machine Learning Fred Lu Joseph Munoz Maya Fuchs Tyler LeBlond Elliott Zaresky-Williams Edward Raff Francis Ferraro Brian Testa FedML 22 35 0 16 Oct 2022
Differentially Private Online-to-Batch for Smooth Losses Qinzi Zhang Hoang Tran Ashok Cutkosky FedML 46 4 0 12 Oct 2022
An Ensemble Teacher-Student Learning Approach with Poisson Sub-sampling to Differential Privacy Preserving Speech Recognition Chao-Han Huck Yang Jun Qi Sabato Marco Siniscalchi Chin-Hui Lee 31 4 0 12 Oct 2022
Momentum Aggregation for Private Non-convex ERM Hoang Tran Ashok Cutkosky 31 14 0 12 Oct 2022
An Experimental Study on Private Aggregation of Teacher Ensemble Learning for End-to-End Speech Recognition Chao-Han Huck Yang I-Fan Chen A. Stolcke Sabato Marco Siniscalchi Chin-Hui Lee 37 2 0 11 Oct 2022
Detecting Backdoors in Deep Text Classifiers Youyan Guo Jun Wang Trevor Cohn SILM 42 1 0 11 Oct 2022
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings Jean Ogier du Terrail Samy Ayed Edwige Cyffers Felix Grimberg Chaoyang He ... Sai Praneeth Karimireddy Marco Lorenzi Giovanni Neglia Marc Tommasi M. Andreux FedML 47 144 0 10 Oct 2022
Differentially Private Deep Learning with ModelMix Hanshen Xiao Jun Wan S. Devadas 31 3 0 07 Oct 2022
CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning Samuel Maddock Alexandre Sablayrolles Pierre Stock FedML 25 22 0 06 Oct 2022
Federated Boosted Decision Trees with Differential Privacy Samuel Maddock Graham Cormode Tianhao Wang Carsten Maple S. Jha FedML 47 29 0 06 Oct 2022
On the Statistical Complexity of Estimation and Testing under Privacy Constraints Clément Lalanne Aurélien Garivier Rémi Gribonval 32 7 0 05 Oct 2022
Fine-Tuning with Differential Privacy Necessitates an Additional Hyperparameter Search Yannis Cattan Christopher A. Choquette-Choo Nicolas Papernot Abhradeep Thakurta 28 20 0 05 Oct 2022
Learning from aggregated data with a maximum entropy model Alexandre Gilotte Ahmed Ben Yahmed D. Rohde FedML OOD 30 0 0 05 Oct 2022
Composition of Differential Privacy & Privacy Amplification by Subsampling Thomas Steinke 79 50 0 02 Oct 2022
PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Model Haiming Wang Zhikun Zhang Tianhao Wang Shibo He Michael Backes Jiming Chen Yang Zhang 51 36 0 02 Oct 2022
Differentially Private Optimization on Large Model at Small Cost Zhiqi Bu Yu Wang Sheng Zha George Karypis 45 52 0 30 Sep 2022
Information Removal at the bottleneck in Deep Neural Networks Enzo Tartaglione 56 2 0 30 Sep 2022
On the Impossible Safety of Large AI Models El-Mahdi El-Mhamdi Sadegh Farhadkhani R. Guerraoui Nirupam Gupta L. Hoang Rafael Pinot Sébastien Rouault John Stephan 37 31 0 30 Sep 2022
Improving alignment of dialogue agents via targeted human judgements Amelia Glaese Nat McAleese Maja Trkebacz John Aslanides Vlad Firoiu ... John F. J. Mellor Demis Hassabis Koray Kavukcuoglu Lisa Anne Hendricks G. Irving ALM AAML 239 507 0 28 Sep 2022
On the Choice of Databases in Differential Privacy Composition Valentin Hartmann Vincent Bindschaedler Robert West 34 0 0 27 Sep 2022
A Snapshot of the Frontiers of Client Selection in Federated Learning Gergely Németh M. Lozano Novi Quadrianto Nuria Oliver FedML 115 14 0 27 Sep 2022
Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy Zhifeng Jiang Wei Wang Ruichuan Chen 48 7 0 26 Sep 2022
Algorithms that Approximate Data Removal: New Results and Limitations Vinith Suriyakumar Ashia Wilson MU 49 27 0 25 Sep 2022
Blinder: End-to-end Privacy Protection in Sensing Systems via Personalized Federated Learning Xin Yang Omid Ardakanian 35 3 0 24 Sep 2022
In Differential Privacy, There is Truth: On Vote Leakage in Ensemble Private Learning Jiaqi Wang R. Schuster Ilia Shumailov David Lie Nicolas Papernot FedML 35 3 0 22 Sep 2022
Distribution inference risks: Identifying and mitigating sources of leakage Valentin Hartmann Léo Meynent Maxime Peyrard Dimitrios Dimitriadis Shruti Tople Robert West MIACV 31 14 0 18 Sep 2022
Non-Imaging Medical Data Synthesis for Trustworthy AI: A Comprehensive Survey Xiaodan Xing Huanjun Wu Lichao Wang Iain Stenson M. Yong Javier Del Ser Simon Walsh Guang Yang 37 7 0 17 Sep 2022
Privacy-Preserving Distributed Expectation Maximization for Gaussian Mixture Model using Subspace Perturbation Qiongxiu Li Jaron Skovsted Gundersen K. Tjell R. Wisniewski M. G. Christensen FedML 10 11 0 16 Sep 2022
Model Inversion Attacks against Graph Neural Networks Zaixin Zhang Qi Liu Zhenya Huang Hao Wang Cheekong Lee Enhong AAML 28 35 0 16 Sep 2022