The Frontiers of Fairness in Machine Learning

20 October 2018

Papers citing "The Frontiers of Fairness in Machine Learning"

32 / 82 papers shown

Title
Fairness in Streaming Submodular Maximization: Algorithms and Hardness Marwa El Halabi Slobodan Mitrović A. Norouzi-Fard Jakab Tardos Jakub Tarnawski 16 47 0 14 Oct 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
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction Stephen R. Pfohl Agata Foryciarz N. Shah FaML 33 108 0 20 Jul 2020
Extending the Machine Learning Abstraction Boundary: A Complex Systems Approach to Incorporate Societal Context Donald Martin Vinodkumar Prabhakaran Jill A. Kuhlberg A. Smart William S. Isaac FaML 14 40 0 17 Jun 2020
A Variational Approach to Privacy and Fairness Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund FaML DRL 19 25 0 11 Jun 2020
DeepFair: Deep Learning for Improving Fairness in Recommender Systems Jesús Bobadilla R. Lara-Cabrera Ángel González-Prieto Fernando Ortega FaML 33 43 0 09 Jun 2020
Statistical Equity: A Fairness Classification Objective Ninareh Mehrabi Yuzhong Huang Fred Morstatter FaML 20 10 0 14 May 2020
Ensuring Fairness under Prior Probability Shifts Arpita Biswas Suvam Mukherjee OOD 24 33 0 06 May 2020
Multilingual Twitter Corpus and Baselines for Evaluating Demographic Bias in Hate Speech Recognition Xiaolei Huang Linzi Xing Franck Dernoncourt Michael J. Paul 16 87 0 24 Feb 2020
Learning Certified Individually Fair Representations Anian Ruoss Mislav Balunović Marc Fischer Martin Vechev FaML 15 92 0 24 Feb 2020
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 24 78 0 24 Feb 2020
Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness Samuel Yeom Matt Fredrikson AAML 19 26 0 18 Feb 2020
Pipeline Interventions Eshwar Ram Arunachaleswaran Sampath Kannan Aaron Roth Juba Ziani 22 7 0 16 Feb 2020
$A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-$\ell_1$-Norm Interpolated Classifiers$ A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum- $\ell_1$ -Norm Interpolated Classifiers Tengyuan Liang Pragya Sur 37 68 0 05 Feb 2020
Algorithmic Fairness Dana Pessach E. Shmueli FaML 33 386 0 21 Jan 2020
Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems C. E. Smith Bowen Yu Anjali Srivastava Aaron L Halfaker Loren G. Terveen Haiyi Zhu KELM 21 69 0 14 Jan 2020
Measurement and Fairness Abigail Z. Jacobs Hanna M. Wallach 14 381 0 11 Dec 2019
Conditional Learning of Fair Representations Han Zhao Amanda Coston T. Adel Geoffrey J. Gordon FaML 27 106 0 16 Oct 2019
Perturbation Sensitivity Analysis to Detect Unintended Model Biases Vinodkumar Prabhakaran Ben Hutchinson Margaret Mitchell 22 117 0 09 Oct 2019
Fairness Warnings and Fair-MAML: Learning Fairly with Minimal Data Dylan Slack Sorelle A. Friedler Emile Givental FaML 32 54 0 24 Aug 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 349 4,237 0 23 Aug 2019
Mitigating Gender Bias in Natural Language Processing: Literature Review Tony Sun Andrew Gaut Shirlyn Tang Yuxin Huang Mai Elsherief Jieyu Zhao Diba Mirza E. Belding-Royer Kai-Wei Chang William Yang Wang AI4CE 47 543 0 21 Jun 2019
Disparate Vulnerability to Membership Inference Attacks B. Kulynych Mohammad Yaghini Giovanni Cherubin Michael Veale Carmela Troncoso 15 39 0 02 Jun 2019
Fairness and Missing Values Fernando Martínez-Plumed Cesar Ferri David Nieves José Hernández-Orallo 16 28 0 29 May 2019
Data Cleaning for Accurate, Fair, and Robust Models: A Big Data - AI Integration Approach Ki Hyun Tae Yuji Roh Young H. Oh Hyunsub Kim Steven Euijong Whang 19 71 0 22 Apr 2019
Scalable Fair Clustering A. Backurs Piotr Indyk Krzysztof Onak B. Schieber A. Vakilian Tal Wagner 33 197 0 10 Feb 2019
Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges Songül Tolan FaML 24 31 0 15 Jan 2019
Differentially Private Fair Learning Matthew Jagielski Michael Kearns Jieming Mao Alina Oprea Aaron Roth Saeed Sharifi-Malvajerdi Jonathan R. Ullman FaML FedML 30 147 0 06 Dec 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 676 0 17 Feb 2018
Matching Code and Law: Achieving Algorithmic Fairness with Optimal Transport Meike Zehlike P. Hacker Emil Wiedemann 21 19 0 21 Dec 2017
Fair Personalization L. E. Celis Nisheeth K. Vishnoi FaML 34 17 0 07 Jul 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,092 0 24 Oct 2016