Differential Privacy Has Disparate Impact on Model Accuracy

28 May 2019

Papers citing "Differential Privacy Has Disparate Impact on Model Accuracy"

50 / 109 papers shown

Title
Modelling the long-term fairness dynamics of data-driven targeted help on job seekers S. Scher Simone Kopeinik A. Trugler Dominik Kowald 45 9 0 17 Aug 2022
Differentially Private Counterfactuals via Functional Mechanism Fan Yang Qizhang Feng Kaixiong Zhou Jiahao Chen Xia Hu 32 8 0 04 Aug 2022
FLAIR: Federated Learning Annotated Image Repository Congzheng Song Filip Granqvist Kunal Talwar FedML 29 28 0 18 Jul 2022
Hercules: Boosting the Performance of Privacy-preserving Federated Learning Guowen Xu Xingshuo Han Shengmin Xu Tianwei Zhang Hongwei Li Xinyi Huang R. Deng FedML 37 16 0 11 Jul 2022
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset Peter Henderson M. Krass Lucia Zheng Neel Guha Christopher D. Manning Dan Jurafsky Daniel E. Ho AILaw ELM 141 98 0 01 Jul 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
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
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models Esma Balkir S. Kiritchenko I. Nejadgholi Kathleen C. Fraser 23 36 0 08 Jun 2022
Differentially Private Shapley Values for Data Evaluation Lauren Watson R. Andreeva Hao Yang Rik Sarkar TDI FAtt FedML 21 6 0 01 Jun 2022
Pruning has a disparate impact on model accuracy Cuong Tran Ferdinando Fioretto Jung-Eun Kim Rakshit Naidu 45 38 0 26 May 2022
On the Importance of Architecture and Feature Selection in Differentially Private Machine Learning Wenxuan Bao L. A. Bauer Vincent Bindschaedler OOD 29 4 0 13 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 29 37 0 08 May 2022
HBFL: A Hierarchical Blockchain-based Federated Learning Framework for a Collaborative IoT Intrusion Detection Mohanad Sarhan Wai Weng Lo S. Layeghy Marius Portmann 28 59 0 08 Apr 2022
Bounding Membership Inference Anvith Thudi Ilia Shumailov Franziska Boenisch Nicolas Papernot 33 18 0 24 Feb 2022
Exploring the Unfairness of DP-SGD Across Settings Frederik Noe R. Herskind Anders Søgaard 27 4 0 24 Feb 2022
Differentially Private Speaker Anonymization Ali Shahin Shamsabadi B. M. L. Srivastava A. Bellet Nathalie Vauquier Emmanuel Vincent Mohamed Maouche Marc Tommasi Nicolas Papernot MIACV 56 33 0 23 Feb 2022
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey Ferdinando Fioretto Cuong Tran Pascal Van Hentenryck Keyu Zhu FaML 32 60 0 16 Feb 2022
Datamodels: Predicting Predictions from Training Data Andrew Ilyas Sung Min Park Logan Engstrom Guillaume Leclerc A. Madry TDI 54 131 0 01 Feb 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification Yuxin Wen Jonas Geiping Liam H. Fowl Micah Goldblum Tom Goldstein FedML 92 93 0 01 Feb 2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges Nuria Rodríguez-Barroso Daniel Jiménez López M. V. Luzón Francisco Herrera Eugenio Martínez-Cámara FedML 37 213 0 20 Jan 2022
Equity and Privacy: More Than Just a Tradeoff David Pujol Ashwin Machanavajjhala 35 15 0 08 Nov 2021
Fairness-Driven Private Collaborative Machine Learning Dana Pessach Tamir Tassa E. Shmueli FedML 33 7 0 29 Sep 2021
NanoBatch Privacy: Enabling fast Differentially Private learning on the IPU Edward H. Lee M. M. Krell Alexander Tsyplikhin Victoria Rege E. Colak Kristen W. Yeom FedML 21 0 0 24 Sep 2021
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data Georgi Ganev Bristena Oprisanu Emiliano De Cristofaro 42 56 0 23 Sep 2021
Partial sensitivity analysis in differential privacy Tamara T. Mueller Alexander Ziller Dmitrii Usynin Moritz Knolle F. Jungmann Daniel Rueckert Georgios Kaissis 50 1 0 22 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 43 16 0 20 Sep 2021
A Fairness Analysis on Private Aggregation of Teacher Ensembles Cuong Tran M. H. Dinh Kyle Beiter Ferdinando Fioretto 21 12 0 17 Sep 2021
Enforcing fairness in private federated learning via the modified method of differential multipliers Borja Rodríguez Gálvez Filip Granqvist Rogier van Dalen M. Seigel FedML 48 52 0 17 Sep 2021
Federated Learning Meets Fairness and Differential Privacy P. Manisha Sankarshan Damle Sujit Gujar FedML 38 21 0 23 Aug 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 32 99 0 10 Aug 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
Smoothed Differential Privacy Ao Liu Yu-Xiang Wang Lirong Xia 33 0 0 04 Jul 2021
Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics Paula Czarnowska Yogarshi Vyas Kashif Shah 21 104 0 28 Jun 2021
Membership Inference on Word Embedding and Beyond Saeed Mahloujifar Huseyin A. Inan Melissa Chase Esha Ghosh Marcello Hasegawa MIACV SILM 25 46 0 21 Jun 2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting Harsha Nori R. Caruana Zhiqi Bu J. Shen Janardhan Kulkarni 38 37 0 17 Jun 2021
Optimality and Stability in Federated Learning: A Game-theoretic Approach Kate Donahue Jon M. Kleinberg FedML 13 45 0 17 Jun 2021
A BIC-based Mixture Model Defense against Data Poisoning Attacks on Classifiers Xi Li David J. Miller Zhen Xiang G. Kesidis AAML 16 0 0 28 May 2021
Model Selection's Disparate Impact in Real-World Deep Learning Applications Jessica Zosa Forde A. Feder Cooper Kweku Kwegyir-Aggrey Chris De Sa Michael Littman 11 22 0 01 Apr 2021
Privacy Regularization: Joint Privacy-Utility Optimization in Language Models Fatemehsadat Mireshghallah Huseyin A. Inan Marcello Hasegawa Victor Rühle Taylor Berg-Kirkpatrick Robert Sim 19 40 0 12 Mar 2021
Understanding and Mitigating Accuracy Disparity in Regression Jianfeng Chi Yuan Tian Geoffrey J. Gordon Han Zhao 27 25 0 24 Feb 2021
Exacerbating Algorithmic Bias through Fairness Attacks Ninareh Mehrabi Muhammad Naveed Fred Morstatter Aram Galstyan AAML 28 67 0 16 Dec 2020
Robustness Threats of Differential Privacy Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets AAML 30 13 0 14 Dec 2020
On the Privacy Risks of Algorithmic Fairness Hong Chang Reza Shokri FaML 38 110 0 07 Nov 2020
Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy Tom Farrand Fatemehsadat Mireshghallah Sahib Singh Andrew Trask FedML 11 88 0 10 Sep 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation Vitaly Feldman Chiyuan Zhang TDI 46 443 0 09 Aug 2020
Anonymizing Machine Learning Models Abigail Goldsteen Gilad Ezov Ron Shmelkin Micha Moffie Ariel Farkash MIACV 19 5 0 26 Jul 2020
Reducing Risk of Model Inversion Using Privacy-Guided Training Abigail Goldsteen Gilad Ezov Ariel Farkash 33 4 0 29 Jun 2020
Model Explanations with Differential Privacy Neel Patel Reza Shokri Yair Zick SILM FedML 28 32 0 16 Jun 2020
Balance is key: Private median splits yield high-utility random trees Shorya Consul Sinead Williamson 17 2 0 15 Jun 2020