Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination

1 June 2019

Papers citing "Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination"

28 / 78 papers shown

Title
Measuring Fairness Under Unawareness of Sensitive Attributes: A Quantification-Based Approach Alessandro Fabris Andrea Esuli Alejandro Moreo Fabrizio Sebastiani 23 18 0 17 Sep 2021
Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in Practice Jiahao Chen Victor Storchan Eren Kurshan 9 10 0 11 Aug 2021
Estimation of Fair Ranking Metrics with Incomplete Judgments Ömer Kirnap Fernando Diaz Asia J. Biega Michael D. Ekstrand Ben Carterette Emine Yilmaz 24 37 0 11 Aug 2021
Interactive Storytelling for Children: A Case-study of Design and Development Considerations for Ethical Conversational AI J. Chubb S. Missaoui S. Concannon Liam Maloney James Alfred Walker 11 29 0 20 Jul 2021
Auditing for Diversity using Representative Examples Vijay Keswani L. E. Celis 22 3 0 15 Jul 2021
Multiaccurate Proxies for Downstream Fairness Emily Diana Wesley Gill Michael Kearns K. Kenthapadi Aaron Roth Saeed Sharifi-Malvajerdi 29 21 0 09 Jul 2021
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data Eugenia Iofinova Nikola Konstantinov Christoph H. Lampert FaML 28 0 0 22 Jun 2021
Fair Classification with Adversarial Perturbations L. E. Celis Anay Mehrotra Nisheeth K. Vishnoi FaML 21 32 0 10 Jun 2021
Fairness-Aware Unsupervised Feature Selection Xiaoying Xing Hongfu Liu Chen Chen Jundong Li FaML 21 12 0 04 Jun 2021
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective Flavien Prost Pranjal Awasthi Nicholas Blumm A. Kumthekar Trevor Potter Li Wei Xuezhi Wang Ed H. Chi Jilin Chen Alex Beutel 43 15 0 20 May 2021
Robust Classification via Support Vector Machines Vali Asimit I. Kyriakou Simone Santoni Salvatore Scognamiglio Rui Zhu AAML OOD 14 3 0 27 Apr 2021
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information Pranjal Awasthi Alex Beutel Matthaeus Kleindessner Jamie Morgenstern Xuezhi Wang FaML 54 55 0 16 Feb 2021
Fairness-Aware PAC Learning from Corrupted Data Nikola Konstantinov Christoph H. Lampert 11 17 0 11 Feb 2021
Removing biased data to improve fairness and accuracy Sahil Verma Michael Ernst René Just FaML 16 24 0 05 Feb 2021
A Statistical Test for Probabilistic Fairness Bahar Taşkesen Jose H. Blanchet Daniel Kuhn Viet Anh Nguyen FaML 14 37 0 09 Dec 2020
Improving Fairness and Privacy in Selection Problems Mohammad Mahdi Khalili Xueru Zhang Mahed Abroshan Somayeh Sojoudi 16 27 0 07 Dec 2020
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty Umang Bhatt Javier Antorán Yunfeng Zhang Q. V. Liao P. Sattigeri ... L. Nachman R. Chunara Madhulika Srikumar Adrian Weller Alice Xiang 19 247 0 15 Nov 2020
Debiasing classifiers: is reality at variance with expectation? Ashrya Agrawal Florian Pfisterer B. Bischl Francois Buet-Golfouse Srijan Sood Jiahao Chen Sameena Shah Sebastian J. Vollmer CML FaML 16 18 0 04 Nov 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 14 328 0 23 Jun 2020
Probabilistic Fair Clustering Seyed-Alireza Esmaeili Brian Brubach Leonidas Tsepenekas John P. Dickerson FaML 16 35 0 19 Jun 2020
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning Esther Rolf Max Simchowitz Sarah Dean Lydia T. Liu Daniel Björkegren Moritz Hardt J. Blumenstock 6 22 0 15 Mar 2020
Fair Learning with Private Demographic Data Hussein Mozannar Mesrob I. Ohannessian Nathan Srebro 25 73 0 26 Feb 2020
Robust Optimization for Fairness with Noisy Protected Groups S. Wang Wenshuo Guo Harikrishna Narasimhan Andrew Cotter Maya R. Gupta Michael I. Jordan NoLa 27 118 0 21 Feb 2020
Algorithmic Fairness Dana Pessach E. Shmueli FaML 33 387 0 21 Jan 2020
Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond Nathan Kallus Xiaojie Mao Masatoshi Uehara 25 25 0 30 Dec 2019
Fairness in Deep Learning: A Computational Perspective Mengnan Du Fan Yang Na Zou Xia Hu FaML FedML 8 229 0 23 Aug 2019
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 192 742 0 13 Dec 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,082 0 24 Oct 2016