Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 1,132 papers shown

Title
When Does Differentially Private Learning Not Suffer in High Dimensions? Xuechen Li Daogao Liu Tatsunori Hashimoto Huseyin A. Inan Janardhan Kulkarni Y. Lee Abhradeep Thakurta 43 58 0 01 Jul 2022
Measuring Forgetting of Memorized Training Examples Matthew Jagielski Om Thakkar Florian Tramèr Daphne Ippolito Katherine Lee ... Eric Wallace Shuang Song Abhradeep Thakurta Nicolas Papernot Chiyuan Zhang TDI 80 102 0 30 Jun 2022
DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware H. Hashemi Yongqin Wang M. Annavaram FedML 28 58 0 30 Jun 2022
Differentially Private Federated Combinatorial Bandits with Constraints Sambhav Solanki Samhita Kanaparthy Sankarshan Damle Sujit Gujar FedML 34 4 0 27 Jun 2022
Libra: High-Utility Anonymization of Event Logs for Process Mining via Subsampling Gamal Elkoumy Marlon Dumas 25 6 0 27 Jun 2022
$k$ -Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy Chenglin Fan Ping Li Xiaoyun Li 39 6 0 26 Jun 2022
Cactus Mechanisms: Optimal Differential Privacy Mechanisms in the Large-Composition Regime Wael Alghamdi S. Asoodeh Flavio du Pin Calmon O. Kosut Lalitha Sankar Fei Wei 21 8 0 25 Jun 2022
FEATHERS: Federated Architecture and Hyperparameter Search Jonas Seng P. Prasad Martin Mundt Devendra Singh Dhami Kristian Kersting FedML 60 3 0 24 Jun 2022
Never trust, always verify : a roadmap for Trustworthy AI? L. Tidjon Foutse Khomh 48 15 0 23 Jun 2022
Beyond Uniform Lipschitz Condition in Differentially Private Optimization Rudrajit Das Satyen Kale Zheng Xu Tong Zhang Sujay Sanghavi 31 17 0 21 Jun 2022
sqSGD: Locally Private and Communication Efficient Federated Learning Yan Feng Tao Xiong Ruofan Wu Lingjuan Lv Leilei Shi FedML 33 2 0 21 Jun 2022
The Privacy Onion Effect: Memorization is Relative Nicholas Carlini Matthew Jagielski Chiyuan Zhang Nicolas Papernot Andreas Terzis Florian Tramèr PILM MIACV 35 102 0 21 Jun 2022
An Efficient Industrial Federated Learning Framework for AIoT: A Face Recognition Application Youlong Ding Xueyang Wu Zhitao Li Zeheng Wu S. Tan Qian Xu Weike Pan Qiang Yang FedML 38 4 0 21 Jun 2022
BlindFL: Vertical Federated Machine Learning without Peeking into Your Data Fangcheng Fu Huanran Xue Yong Cheng Yangyu Tao Tengjiao Wang FedML 26 59 0 16 Jun 2022
On Privacy and Personalization in Cross-Silo Federated Learning Ziyu Liu Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 34 53 0 16 Jun 2022
Reconstructing Training Data from Trained Neural Networks Niv Haim Gal Vardi Gilad Yehudai Ohad Shamir Michal Irani 45 132 0 15 Jun 2022
Disparate Impact in Differential Privacy from Gradient Misalignment Maria S. Esipova Atiyeh Ashari Ghomi Yaqiao Luo Jesse C. Cresswell 29 25 0 15 Jun 2022
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints Justin Whitehouse Zhiwei Steven Wu Aaditya Ramdas Ryan M. Rogers 16 9 0 15 Jun 2022
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger Zhiqi Bu Yu Wang Sheng Zha George Karypis 37 69 0 14 Jun 2022
Self-Supervised Pretraining for Differentially Private Learning Arash Asadian Evan Weidner Lei Jiang PICV 35 3 0 14 Jun 2022
Neurotoxin: Durable Backdoors in Federated Learning Zhengming Zhang Ashwinee Panda Linyue Song Yaoqing Yang Michael W. Mahoney Joseph E. Gonzalez Kannan Ramchandran Prateek Mittal FedML 43 130 0 12 Jun 2022
NeuGuard: Lightweight Neuron-Guided Defense against Membership Inference Attacks Nuo Xu Binghui Wang Ran Ran Wujie Wen Parv Venkitasubramaniam AAML 31 5 0 11 Jun 2022
Bayesian Estimation of Differential Privacy Santiago Zanella Béguelin Lukas Wutschitz Shruti Tople A. Salem Victor Rühle Andrew Paverd Mohammad Naseri Boris Köpf Daniel Jones 30 36 0 10 Jun 2022
Deep Leakage from Model in Federated Learning Zihao Zhao Mengen Luo Wenbo Ding FedML 26 14 0 10 Jun 2022
Analytical Composition of Differential Privacy via the Edgeworth Accountant Hua Wang Sheng-yang Gao Huanyu Zhang Milan Shen Weijie J. Su FedML 36 21 0 09 Jun 2022
Gradient Obfuscation Gives a False Sense of Security in Federated Learning Kai Yue Richeng Jin Chau-Wai Wong D. Baron H. Dai FedML 40 46 0 08 Jun 2022
Subject Membership Inference Attacks in Federated Learning Anshuman Suri Pallika H. Kanani Virendra J. Marathe Daniel W. Peterson 30 25 0 07 Jun 2022
Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization Yi Ma T. V. Marinov Tong Zhang 32 8 0 03 Jun 2022
On the Privacy Properties of GAN-generated Samples Zinan Lin Vyas Sekar Giulia Fanti PICV 24 26 0 03 Jun 2022
Impact of Sampling on Locally Differentially Private Data Collection Sayan Biswas Graham Cormode Carsten Maple FedML 35 0 0 02 Jun 2022
A Blessing of Dimensionality in Membership Inference through Regularization Jasper Tan Daniel LeJeune Blake Mason Hamid Javadi Richard G. Baraniuk 34 18 0 27 May 2022
Auditing Differential Privacy in High Dimensions with the Kernel Quantum Rényi Divergence Carles Domingo-Enrich Youssef Mroueh 27 5 0 27 May 2022
Generating multivariate time series with COmmon Source CoordInated GAN (COSCI-GAN) Ali Seyfi Jean-Francois Rajotte Raymond T. Ng AI4TS 16 27 0 27 May 2022
Membership Inference Attack Using Self Influence Functions Gilad Cohen Raja Giryes TDI 32 12 0 26 May 2022
VeriFi: Towards Verifiable Federated Unlearning Xiangshan Gao Xingjun Ma Jingyi Wang Youcheng Sun Bo Li S. Ji Peng Cheng Jiming Chen MU 75 46 0 25 May 2022
Are Large Pre-Trained Language Models Leaking Your Personal Information? Jie Huang Hanyin Shao Kevin Chen-Chuan Chang PILM 22 178 0 25 May 2022
Additive Logistic Mechanism for Privacy-Preserving Self-Supervised Learning Yunhao Yang Parham Gohari Ufuk Topcu 31 1 0 25 May 2022
CryptoTL: Private, Efficient and Secure Transfer Learning Roman Walch Samuel Sousa Lukas Helminger Stefanie N. Lindstaedt Christian Rechberger A. Trugler 38 8 0 24 May 2022
PrivFairFL: Privacy-Preserving Group Fairness in Federated Learning Sikha Pentyala Nicola Neophytou A. Nascimento Martine De Cock G. Farnadi 47 17 0 23 May 2022
LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation Ljubomir Rokvic Panayiotis Danassis Sai Praneeth Karimireddy Boi Faltings TDI 37 1 0 23 May 2022
Time-series Transformer Generative Adversarial Networks Padmanaba Srinivasan William J. Knottenbelt AI4TS 28 13 0 23 May 2022
FaceMAE: Privacy-Preserving Face Recognition via Masked Autoencoders Kaidi Wang Bo Zhao Xiangyu Peng Zheng Hua Zhu Jiankang Deng Xinchao Wang Hakan Bilen Yang You PICV 58 11 0 23 May 2022
Differential Privacy: What is all the noise about? Roxana Dánger Mercaderes 43 3 0 19 May 2022
Recovering Private Text in Federated Learning of Language Models Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 40 75 0 17 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 47 104 0 16 May 2022
On the Importance of Architecture and Feature Selection in Differentially Private Machine Learning Wenxuan Bao L. A. Bauer Vincent Bindschaedler OOD 34 4 0 13 May 2022
Secure Aggregation for Federated Learning in Flower Kwing Hei Li Pedro Porto Buarque de Gusmão Daniel J. Beutel Nicholas D. Lane FedML 37 36 0 12 May 2022
Blockchain-based Secure Client Selection in Federated Learning Truc D. T. Nguyen Phuc Thai Tre' R. Jeter Thang N. Dinh My T. Thai 33 12 0 11 May 2022
Privacy Enhancement for Cloud-Based Few-Shot Learning Archit Parnami Muhammad Usama Liyue Fan Minwoo Lee 27 1 0 10 May 2022
Decentralized Stochastic Optimization with Inherent Privacy Protection Yongqiang Wang H. Vincent Poor 31 37 0 08 May 2022