Differentially Private Fair Learning

6 December 2018

Saeed Sharifi-Malvajerdi

Papers citing "Differentially Private Fair Learning"

39 / 89 papers shown

Title
Fairness-Driven Private Collaborative Machine Learning Dana Pessach Tamir Tassa E. Shmueli FedML 33 7 0 29 Sep 2021
A Sociotechnical View of Algorithmic Fairness Mateusz Dolata Stefan Feuerriegel Gerhard Schwabe FaML 32 94 0 27 Sep 2021
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data Georgi Ganev Bristena Oprisanu Emiliano De Cristofaro 39 56 0 23 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
Statistical Guarantees for Fairness Aware Plug-In Algorithms Drona Khurana S. Ravichandran Sparsh Jain N. Edakunni FaML 12 0 0 27 Jul 2021
Multiaccurate Proxies for Downstream Fairness Emily Diana Wesley Gill Michael Kearns K. Kenthapadi Aaron Roth Saeed Sharifi-Malvajerdi 35 21 0 09 Jul 2021
DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accuracy? Archit Uniyal Rakshit Naidu Sasikanth Kotti Sahib Singh Patrik Kenfack Fatemehsadat Mireshghallah Andrew Trask 19 33 0 22 Jun 2021
Fair Normalizing Flows Mislav Balunović Anian Ruoss Martin Vechev AAML 22 36 0 10 Jun 2021
Decision Making with Differential Privacy under a Fairness Lens Ferdinando Fioretto Cuong Tran Pascal Van Hentenryck 32 46 0 16 May 2021
A Stochastic Optimization Framework for Fair Risk Minimization Andrew Lowy Sina Baharlouei Rakesh Pavan Meisam Razaviyayn Ahmad Beirami FaML 30 21 0 24 Feb 2021
Investigating Trade-offs in Utility, Fairness and Differential Privacy in Neural Networks Marlotte Pannekoek G. Spigler FedML 32 26 0 11 Feb 2021
Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities Nenad Tomašev Kevin R. McKee Jackie Kay Shakir Mohamed FaML 30 86 0 03 Feb 2021
Exacerbating Algorithmic Bias through Fairness Attacks Ninareh Mehrabi Muhammad Naveed Fred Morstatter Aram Galstyan AAML 28 67 0 16 Dec 2020
Improving Fairness and Privacy in Selection Problems Mohammad Mahdi Khalili Xueru Zhang Mahed Abroshan Somayeh Sojoudi 21 27 0 07 Dec 2020
On the Privacy Risks of Algorithmic Fairness Hong Chang Reza Shokri FaML 38 110 0 07 Nov 2020
"What We Can't Measure, We Can't Understand": Challenges to Demographic Data Procurement in the Pursuit of Fairness Mckane Andrus Elena Spitzer Jeffrey Brown Alice Xiang 29 126 0 30 Oct 2020
Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness Lingjuan Lyu Xuanli He Yitong Li 35 89 0 03 Oct 2020
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach Cuong Tran Ferdinando Fioretto Pascal Van Hentenryck FedML 29 78 0 26 Sep 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
Collaborative Fairness in Federated Learning Lingjuan Lyu Xinyi Xu Qian Wang FedML 6 188 0 27 Aug 2020
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence Tianqing Zhu Dayong Ye Wei Wang Wanlei Zhou Philip S. Yu SyDa 38 125 0 05 Aug 2020
How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning Lingjuan Lyu Yitong Li Karthik Nandakumar Jiangshan Yu Xingjun Ma FedML 6 49 0 18 Jul 2020
Fairness without Demographics through Adversarially Reweighted Learning Preethi Lahoti Alex Beutel Jilin Chen Kang Lee Flavien Prost Nithum Thain Xuezhi Wang Ed H. Chi FaML 19 329 0 23 Jun 2020
Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy Bashir Rastegarpanah M. Crovella Krishna P. Gummadi FaML 21 8 0 19 May 2020
Statistical Equity: A Fairness Classification Objective Ninareh Mehrabi Yuzhong Huang Fred Morstatter FaML 20 10 0 14 May 2020
Fair Learning with Private Demographic Data Hussein Mozannar Mesrob I. Ohannessian Nathan Srebro 35 73 0 26 Feb 2020
Learning Certified Individually Fair Representations Anian Ruoss Mislav Balunović Marc Fischer Martin Vechev FaML 15 92 0 24 Feb 2020
Boosted and Differentially Private Ensembles of Decision Trees Richard Nock Wilko Henecka 6 2 0 26 Jan 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 76 6,103 0 10 Dec 2019
On the Legal Compatibility of Fairness Definitions Alice Xiang Inioluwa Deborah Raji AILaw FaML 11 58 0 25 Nov 2019
Auditing and Achieving Intersectional Fairness in Classification Problems Giulio Morina V. Oliinyk J. Waton Ines Marusic K. Georgatzis FaML 19 39 0 04 Nov 2019
Fault Tolerance of Neural Networks in Adversarial Settings Vasisht Duddu N. Pillai D. V. Rao V. Balas SILM AAML 27 11 0 30 Oct 2019
The Cost of a Reductions Approach to Private Fair Optimization Daniel Alabi 41 3 0 23 Jun 2019
Towards Fair and Privacy-Preserving Federated Deep Models Lingjuan Lyu Jiangshan Yu Karthik Nandakumar Yitong Li Xingjun Ma Jiong Jin Han Yu Kee Siong Ng FedML 16 20 0 04 Jun 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 10 467 0 28 May 2019
Multi-Differential Fairness Auditor for Black Box Classifiers Xavier Gitiaux Huzefa Rangwala FaML 14 7 0 18 Mar 2019
Noise-tolerant fair classification A. Lamy Ziyuan Zhong A. Menon Nakul Verma NoLa 15 76 0 30 Jan 2019
An Intersectional Definition of Fairness James R. Foulds Rashidul Islam Kamrun Naher Keya Shimei Pan FaML 21 186 0 22 Jul 2018