Deep Learning with Label Differential Privacy

11 February 2021

Papers citing "Deep Learning with Label Differential Privacy"

50 / 100 papers shown

Title
Differentially-Private Decision Trees and Provable Robustness to Data Poisoning D. Vos Jelle Vos Tianyu Li Z. Erkin S. Verwer FedML 11 1 0 24 May 2023
Personalized DP-SGD using Sampling Mechanisms Geon Heo Junseok Seo Steven Euijong Whang 12 2 0 24 May 2023
Evaluating Privacy Leakage in Split Learning Xinchi Qiu Ilias Leontiadis Luca Melis Alex Sablayrolles Pierre Stock 17 5 0 22 May 2023
On the Fairness Impacts of Private Ensembles Models Cuong Tran Ferdinando Fioretto 31 4 0 19 May 2023
PrivaScissors: Enhance the Privacy of Collaborative Inference through the Lens of Mutual Information Lin Duan Jingwei Sun Yiran Chen M. Gorlatova 16 2 0 17 May 2023
Learning from Aggregated Data: Curated Bags versus Random Bags Lin Chen Gang Fu Amin Karbasi Vahab Mirrokni FedML 43 10 0 16 May 2023
MetaMorphosis: Task-oriented Privacy Cognizant Feature Generation for Multi-task Learning Md. Adnan Arefeen Zhouyu Li M. Y. S. Uddin Anupam Das 22 0 0 13 May 2023
DPMLBench: Holistic Evaluation of Differentially Private Machine Learning Chengkun Wei Ming-Hui Zhao Zhikun Zhang Min Chen Wenlong Meng Bodong Liu Yuan-shuo Fan Wenzhi Chen 22 11 0 10 May 2023
Differentially Private Attention Computation Yeqi Gao Zhao-quan Song Xin Yang 42 19 0 08 May 2023
Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties Jingwei Sun Zhixu Du Anna Dai Saleh Baghersalimi Alireza Amirshahi David Atienza Yiran Chen FedML 9 6 0 28 Mar 2023
Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples Jingwei Sun Ziyue Xu Dong Yang V. Nath Wenqi Li Can Zhao Daguang Xu Yiran Chen H. Roth FedML 19 14 0 28 Mar 2023
PRIMO: Private Regression in Multiple Outcomes Seth Neel 23 0 0 07 Mar 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 94 167 0 01 Mar 2023
On Provable Copyright Protection for Generative Models Nikhil Vyas Sham Kakade Boaz Barak 10 87 0 21 Feb 2023
Learning From Biased Soft Labels Hua Yuan Ning Xu Yuge Shi Xin Geng Yong Rui FedML 16 6 0 16 Feb 2023
Label Inference Attack against Split Learning under Regression Setting Shangyu Xie Xin Yang Yuanshun Yao Tianyi Liu Taiqing Wang Jiankai Sun FedML 16 9 0 18 Jan 2023
Simple Binary Hypothesis Testing under Local Differential Privacy and Communication Constraints Ankit Pensia Amir-Reza Asadi Varun Jog Po-Ling Loh 12 12 0 09 Jan 2023
Regression with Label Differential Privacy Badih Ghazi Pritish Kamath Ravi Kumar Ethan Leeman Pasin Manurangsi A. Varadarajan Chiyuan Zhang 16 18 0 12 Dec 2022
PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels Huaxi Huang Hui-Sung Kang Sheng Liu Olivier Salvado Thierry Rakotoarivelo Dadong Wang Tongliang Liu NoLa 20 7 0 07 Dec 2022
Vertical Federated Learning: A Structured Literature Review Afsana Khan M. T. Thij A. Wilbik FedML 25 9 0 01 Dec 2022
Private Ad Modeling with DP-SGD Carson E. Denison Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Krishnagiri Narra Amer Sinha A. Varadarajan Chiyuan Zhang 19 14 0 21 Nov 2022
Private Data Valuation and Fair Payment in Data Marketplaces Zhihua Tian Jian-wei Liu J. Li Xinle Cao R. Jia Jun Kong Mengdi Liu Kui Ren TDI 19 12 0 17 Oct 2022
Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes Zhaowei Zhu Yuanshun Yao Jiankai Sun Hanguang Li Y. Liu 14 21 0 06 Oct 2022
DPAUC: Differentially Private AUC Computation in Federated Learning Jiankai Sun Xin Yang Yuanshun Yao Junyuan Xie Di Wu Chong-Jun Wang FedML 17 11 0 25 Aug 2022
Differentially Private Partial Set Cover with Applications to Facility Location George Z. Li Dung Nguyen A. Vullikanti 16 4 0 21 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 34 102 0 30 Jun 2022
How unfair is private learning ? Amartya Sanyal Yaxian Hu Fanny Yang FaML FedML 14 22 0 08 Jun 2022
FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning Meisam Hejazinia Dzmitry Huba Ilias Leontiadis Kiwan Maeng Mani Malek Luca Melis Ilya Mironov Milad Nasr Kaikai Wang Carole-Jean Wu FedML 9 5 0 07 Jun 2022
Differentially Private AUC Computation in Vertical Federated Learning Jiankai Sun Xin Yang Yuanshun Yao Junyuan Xie Di Wu Chong-Jun Wang FedML 35 5 0 24 May 2022
GeoPointGAN: Synthetic Spatial Data with Local Label Differential Privacy Teddy Cunningham Konstantin Klemmer Hongkai Wen Hakan Ferhatosmanoglu 4 10 0 18 May 2022
Differentially Private Learning with Margin Guarantees Raef Bassily M. Mohri A. Suresh 15 9 0 21 Apr 2022
Just Fine-tune Twice: Selective Differential Privacy for Large Language Models Weiyan Shi Ryan Shea Si-An Chen Chiyuan Zhang R. Jia Zhou Yu AAML 18 38 0 15 Apr 2022
Similarity-based Label Inference Attack against Training and Inference of Split Learning Junlin Liu Xinchen Lyu Qimei Cui Xiaofeng Tao FedML 11 26 0 10 Mar 2022
Differentially Private Label Protection in Split Learning Xin Yang Jiankai Sun Yuanshun Yao Junyuan Xie Chong-Jun Wang FedML 26 36 0 04 Mar 2022
Label Leakage and Protection from Forward Embedding in Vertical Federated Learning Jiankai Sun Xin Yang Yuanshun Yao Chong-Jun Wang FedML 11 37 0 02 Mar 2022
Does Label Differential Privacy Prevent Label Inference Attacks? Ruihan Wu Jinfu Zhou Kilian Q. Weinberger Chuan Guo 13 15 0 25 Feb 2022
ExPLoit: Extracting Private Labels in Split Learning Sanjay Kariyappa Moinuddin K. Qureshi FedML 20 22 0 25 Nov 2021
Masked LARk: Masked Learning, Aggregation and Reporting worKflow Joseph J. Pfeiffer Denis Xavier Charles Davis Gilton Young Hun Jung Mehul Parsana Erik Anderson 16 11 0 27 Oct 2021
Label differential privacy via clustering Hossein Esfandiari Vahab Mirrokni Umar Syed Sergei Vassilvitskii FedML 11 26 0 05 Oct 2021
Antipodes of Label Differential Privacy: PATE and ALIBI Mani Malek Ilya Mironov Karthik Prasad I. Shilov Florian Tramèr 8 62 0 07 Jun 2021
A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep Learning Yuexin Xiang Tiantian Li Wei Ren Tianqing Zhu Kim-Kwang Raymond Choo 28 4 0 19 May 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 295 5,761 0 29 Apr 2021
Leveraging Public Data for Practical Private Query Release Terrance Liu G. Vietri Thomas Steinke Jonathan R. Ullman Zhiwei Steven Wu 148 58 0 17 Feb 2021
Label Leakage and Protection in Two-party Split Learning Oscar Li Jiankai Sun Xin Yang Weihao Gao Hongyi Zhang Junyuan Xie Virginia Smith Chong-Jun Wang FedML 122 139 0 17 Feb 2021
Privacy-preserving Data Sharing on Vertically Partitioned Data Razane Tajeddine Joonas Jälkö Samuel Kaski Antti Honkela FedML 16 8 0 19 Oct 2020
Individual Privacy Accounting via a Renyi Filter Vitaly Feldman Tijana Zrnic 46 86 0 25 Aug 2020
Tempered Sigmoid Activations for Deep Learning with Differential Privacy Nicolas Papernot Abhradeep Thakurta Shuang Song Steve Chien Ulfar Erlingsson AAML 128 178 0 28 Jul 2020
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 134 420 0 29 Nov 2018
Efficient Per-Example Gradient Computations Ian Goodfellow 166 73 0 07 Oct 2015
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 99 571 0 08 Dec 2012