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Deep Learning with Differential Privacy

1 July 2016

Papers citing "Deep Learning with Differential Privacy"

50 / 2,788 papers shown

Title
Differentially Private Representation Learning via Image Captioning Tom Sander Yaodong Yu Maziar Sanjabi Alain Durmus Yi-An Ma Kamalika Chaudhuri Chuan Guo 106 4 0 04 Mar 2024
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks Sayedeh Leila Noorbakhsh Binghui Zhang Yuan Hong Binghui Wang AAML 117 11 0 04 Mar 2024
Differentially Private Synthetic Data via Foundation Model APIs 2: Text Chulin Xie Zinan Lin A. Backurs Sivakanth Gopi Da Yu ... Haotian Jiang Huishuai Zhang Yin Tat Lee Yue Liu Sergey Yekhanin SyDa 115 45 0 04 Mar 2024
Enhancing Data Provenance and Model Transparency in Federated Learning Systems -- A Database Approach Michael Gu Ramasoumya Naraparaju Dongfang Zhao FedML 86 0 0 03 Mar 2024
Privacy-Preserving Collaborative Split Learning Framework for Smart Grid Load Forecasting Asif Iqbal P. Gope Biplab Sikdar 87 2 0 03 Mar 2024
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach Qi Tan Qi Li Yi Zhao Zhuotao Liu Xiaobing Guo Ke Xu FedML 87 3 0 02 Mar 2024
Differentially Private Knowledge Distillation via Synthetic Text Generation James Flemings Murali Annavaram SyDa 85 14 0 01 Mar 2024
Blockchain-empowered Federated Learning: Benefits, Challenges, and Solutions Zeju Cai Jianguo Chen Yuting Fan Zibin Zheng Keqin Li 83 8 0 01 Mar 2024
Teach LLMs to Phish: Stealing Private Information from Language Models Ashwinee Panda Christopher A. Choquette-Choo Zhengming Zhang Yaoqing Yang Prateek Mittal PILM 118 28 0 01 Mar 2024
Shifted Interpolation for Differential Privacy Jinho Bok Weijie Su Jason M. Altschuler 131 9 0 01 Mar 2024
SPriFed-OMP: A Differentially Private Federated Learning Algorithm for Sparse Basis Recovery Ajinkya Kiran Mulay Xiaojun Lin 66 0 0 29 Feb 2024
On the Convergence of Differentially-Private Fine-tuning: To Linearly Probe or to Fully Fine-tune? Shuqi Ke Charlie Hou Giulia Fanti Sewoong Oh 87 5 0 29 Feb 2024
Pre-training Differentially Private Models with Limited Public Data Zhiqi Bu Xinwei Zhang Mingyi Hong Sheng Zha George Karypis 137 4 0 28 Feb 2024
Unveiling Privacy, Memorization, and Input Curvature Links Deepak Ravikumar Efstathia Soufleri Abolfazl Hashemi Kaushik Roy 119 6 0 28 Feb 2024
Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence Ilyas Fatkhullin Niao He 80 4 0 27 Feb 2024
LLM-based Privacy Data Augmentation Guided by Knowledge Distillation with a Distribution Tutor for Medical Text Classification Yiping Song Juhua Zhang Zhiliang Tian Yuxin Yang Minlie Huang Dongsheng Li 85 11 0 26 Feb 2024
State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey Chaoyu Zhang Shaoyu Li AILaw 151 4 0 25 Feb 2024
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study Natalija Mitic Apostolos Pyrgelis Sinem Sav FedML 110 1 0 25 Feb 2024
Differentially Private Fair Binary Classifications Hrad Ghoukasian S. Asoodeh FaML 100 2 0 23 Feb 2024
Closed-Form Bounds for DP-SGD against Record-level Inference Giovanni Cherubin Boris Köpf Andrew Paverd Shruti Tople Lukas Wutschitz Santiago Zanella Béguelin 99 2 0 22 Feb 2024
Protect and Extend -- Using GANs for Synthetic Data Generation of Time-Series Medical Records Navid Ashrafi Vera Schmitt R. Spang Sebastian Möller Jan-Niklas Voigt-Antons SyDa 73 7 0 21 Feb 2024
Privacy-Preserving Instructions for Aligning Large Language Models Da Yu Peter Kairouz Sewoong Oh Zheng Xu 132 25 0 21 Feb 2024
Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation Gavin Brown Krishnamurthy Dvijotham Georgina Evans Daogao Liu Adam D. Smith Abhradeep Thakurta 118 6 0 21 Feb 2024
Revisiting Differentially Private Hyper-parameter Tuning Zihang Xiang Tianhao Wang Cheng-Long Wang Di Wang 119 7 0 20 Feb 2024
Bounding Reconstruction Attack Success of Adversaries Without Data Priors Alexander Ziller Anneliese Riess Kristian Schwethelm Tamara T. Mueller Daniel Rueckert Georgios Kaissis MIACV AAML 69 1 0 20 Feb 2024
Amplifying Training Data Exposure through Fine-Tuning with Pseudo-Labeled Memberships Myung Gyo Oh Hong Eun Ahn L. Park T.-H. Kwon MIALM AAML 102 0 0 19 Feb 2024
Neural Networks with (Low-Precision) Polynomial Approximations: New Insights and Techniques for Accuracy Improvement Chi Zhang Jingjing Fan Man Ho Au Siu-Ming Yiu 109 1 0 17 Feb 2024
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization Andrew Lowy Jonathan R. Ullman Stephen J. Wright 110 8 0 17 Feb 2024
Proving membership in LLM pretraining data via data watermarks Johnny Tian-Zheng Wei Ryan Yixiang Wang Robin Jia WaLM 139 33 0 16 Feb 2024
TernaryVote: Differentially Private, Communication Efficient, and Byzantine Resilient Distributed Optimization on Heterogeneous Data Richeng Jin Yujie Gu Kai Yue Xiaofan He Zhaoyang Zhang Huaiyu Dai FedML 76 0 0 16 Feb 2024
Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy Songjie Xie Youlong Wu Jiaxuan Li Ming Ding Khaled B. Letaief AAML 74 1 0 16 Feb 2024
A chaotic maps-based privacy-preserving distributed deep learning for incomplete and Non-IID datasets Irina Arévalo Jose L. Salmeron FedML 66 4 0 15 Feb 2024
Benchmarking federated strategies in Peer-to-Peer Federated learning for biomedical data Jose L. Salmeron Irina Arévalo A. Ruiz-Celma OOD FedML 143 14 0 15 Feb 2024
DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service Yu Liu Zibo Wang Yifei Zhu Chen Chen FedML 60 3 0 15 Feb 2024
Auditing Private Prediction Karan Chadha Matthew Jagielski Nicolas Papernot Christopher A. Choquette-Choo Milad Nasr 128 8 0 14 Feb 2024
Momentum Approximation in Asynchronous Private Federated Learning Tao Yu Congzheng Song Jianyu Wang Mona Chitnis FedML 105 1 0 14 Feb 2024
Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training Tom Sander Maxime Sylvestre Alain Durmus 76 1 0 13 Feb 2024
Data Reconstruction Attacks and Defenses: A Systematic Evaluation Sheng Liu Zihan Wang Yuxiao Chen Qi Lei AAML MIACV 118 4 0 13 Feb 2024
PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining Mishaal Kazmi H. Lautraite Alireza Akbari Mauricio Soroco Qiaoyue Tang Tao Wang Sébastien Gambs Mathias Lécuyer 95 11 0 12 Feb 2024
Do Membership Inference Attacks Work on Large Language Models? Michael Duan Anshuman Suri Niloofar Mireshghallah Sewon Min Weijia Shi Luke Zettlemoyer Yulia Tsvetkov Yejin Choi David Evans Hanna Hajishirzi MIALM 148 103 0 12 Feb 2024
Differentially Private Zeroth-Order Methods for Scalable Large Language Model Finetuning Zhicheng Liu Jian Lou Wenxuan Bao Yihan Hu Baochun Li Zhan Qin K. Ren 124 10 0 12 Feb 2024
Privacy-Optimized Randomized Response for Sharing Multi-Attribute Data Akito Yamamoto Tetsuo Shibuya 37 2 0 12 Feb 2024
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off Yuecheng Li Lele Fu Tong Wang Jian Lou Bin Chen Lei Yang Zibin Zheng Zibin Zheng Chuan Chen FedML 123 4 0 10 Feb 2024
RQP-SGD: Differential Private Machine Learning through Noisy SGD and Randomized Quantization Ce Feng Parv Venkitasubramaniam 85 1 0 09 Feb 2024
On Differentially Private Subspace Estimation in a Distribution-Free Setting Eliad Tsfadia 97 2 0 09 Feb 2024
Privacy Profiles for Private Selection Antti Koskela Rachel Redberg Yu-Xiang Wang 113 2 0 09 Feb 2024
On the Privacy of Selection Mechanisms with Gaussian Noise Jonathan Lebensold Doina Precup Borja Balle 78 0 0 09 Feb 2024
Towards Biologically Plausible and Private Gene Expression Data Generation Dingfan Chen Marie Oestreich Tejumade Afonja Raouf Kerkouche Matthias Becker Mario Fritz SyDa 78 4 0 07 Feb 2024
Advancing Explainable AI Toward Human-Like Intelligence: Forging the Path to Artificial Brain Yongchen Zhou Richard Jiang 68 4 0 07 Feb 2024
Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data Yvonne Zhou Mingyu Liang Shubham Sharma Dana Dachman-Soled Danial Dervovic Antigoni Polychroniadou Min Wu 90 1 0 06 Feb 2024