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Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

14 November 2017

Papers citing "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness"

50 / 448 papers shown

Title
Opportunistic Multi-aspect Fairness through Personalized Re-ranking Nasim Sonboli Farzad Eskandanian Robin Burke Weiwen Liu B. Mobasher FaML 48 47 0 21 May 2020
Sample Complexity of Uniform Convergence for Multicalibration Eliran Shabat Lee Cohen Yishay Mansour FaML 75 28 0 04 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 120 382 0 30 Apr 2020
Genetic programming approaches to learning fair classifiers William La Cava J. Moore FaML 62 19 0 28 Apr 2020
The Impact of Presentation Style on Human-In-The-Loop Detection of Algorithmic Bias Po-Ming Law Sana Malik F. Du Moumita Sinha 45 6 0 26 Apr 2020
Individual Fairness in Pipelines Cynthia Dwork Christina Ilvento Meena Jagadeesan FaML 58 40 0 12 Apr 2020
Abstracting Fairness: Oracles, Metrics, and Interpretability Cynthia Dwork Christina Ilvento G. Rothblum Pragya Sur FaML 83 8 0 04 Apr 2020
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret Vishnu Suresh Lokhande A. K. Akash Sathya Ravi Vikas Singh FaML 52 31 0 03 Apr 2020
A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set Philippe C. Besse E. del Barrio Paula Gordaliza Jean-Michel Loubes Laurent Risser FaML 70 66 0 31 Mar 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 43 23 0 15 Mar 2020
Learning Certified Individually Fair Representations Anian Ruoss Mislav Balunović Marc Fischer Martin Vechev FaML 73 96 0 24 Feb 2020
Fair Prediction with Endogenous Behavior Christopher Jung Sampath Kannan Changhwa Lee Mallesh M. Pai Aaron Roth R. Vohra FaML 55 38 0 18 Feb 2020
Metric-Free Individual Fairness in Online Learning Yahav Bechavod Christopher Jung Zhiwei Steven Wu FaML 120 50 0 13 Feb 2020
To Split or Not to Split: The Impact of Disparate Treatment in Classification Hao Wang Hsiang Hsu Mario Díaz Flavio du Pin Calmon 128 23 0 12 Feb 2020
Deontological Ethics By Monotonicity Shape Constraints S. Wang Maya R. Gupta 69 21 0 31 Jan 2020
Lagrangian Duality for Constrained Deep Learning Ferdinando Fioretto Pascal Van Hentenryck Terrence W.K. Mak Cuong Tran Federico Baldo M. Lombardi PINN 62 84 0 26 Jan 2020
On the Fairness of Randomized Trials for Recommendation with Heterogeneous Demographics and Beyond Zifeng Wang Xi Chen Rui Wen Shao-Lun Huang 139 1 0 25 Jan 2020
Theory In, Theory Out: The uses of social theory in machine learning for social science J. Radford K. Joseph 61 44 0 09 Jan 2020
Learning from Discriminatory Training Data Przemyslaw A. Grabowicz Nicholas Perello Kenta Takatsu FaML 97 1 0 17 Dec 2019
On the Apparent Conflict Between Individual and Group Fairness Reuben Binns FaML 118 316 0 14 Dec 2019
Group Fairness in Bandit Arm Selection Candice Schumann Zhi Lang Nicholas Mattei John P. Dickerson FaML 90 15 0 09 Dec 2019
Fair Data Adaptation with Quantile Preservation Drago Plečko N. Meinshausen 69 30 0 15 Nov 2019
Auditing and Achieving Intersectional Fairness in Classification Problems Giulio Morina V. Oliinyk J. Waton Ines Marusic K. Georgatzis FaML 82 41 0 04 Nov 2019
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers Ananth Balashankar Alyssa Lees Chris Welty L. Subramanian 85 21 0 30 Oct 2019
Toward a better trade-off between performance and fairness with kernel-based distribution matching Flavien Prost Hai Qian Qiuwen Chen Ed H. Chi Jilin Chen Alex Beutel FaML 75 44 0 25 Oct 2019
Fairness Sample Complexity and the Case for Human Intervention Ananth Balashankar Alyssa Lees 31 3 0 24 Oct 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 342 6,391 0 22 Oct 2019
Keeping Designers in the Loop: Communicating Inherent Algorithmic Trade-offs Across Multiple Objectives Bowen Yu Ye Yuan Loren G. Terveen Zhiwei Steven Wu Jodi Forlizzi Haiyi Zhu 80 2 0 07 Oct 2019
Group-based Fair Learning Leads to Counter-intuitive Predictions Ofir Nachum Heinrich Jiang FaML 45 2 0 04 Oct 2019
What does it mean to solve the problem of discrimination in hiring? Social, technical and legal perspectives from the UK on automated hiring systems Javier Sánchez-Monedero L. Dencik L. Edwards 92 138 0 28 Sep 2019
Generating Fair Universal Representations using Adversarial Models Peter Kairouz Jiachun Liao Chong Huang Maunil R. Vyas Monica Welfert Lalitha Sankar 101 17 0 27 Sep 2019
Advancing subgroup fairness via sleeping experts Avrim Blum Thodoris Lykouris FedML 68 37 0 18 Sep 2019
Learning Fair Rule Lists Ulrich Aïvodji Julien Ferry Sébastien Gambs Marie-José Huguet Mohamed Siala FaML 67 11 0 09 Sep 2019
Optimizing Generalized Rate Metrics through Game Equilibrium Harikrishna Narasimhan Andrew Cotter Maya R. Gupta 57 4 0 06 Sep 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 622 4,430 0 23 Aug 2019
Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Laurent Risser Alberto González Sanz Quentin Vincenot Jean-Michel Loubes 100 21 0 15 Aug 2019
Wasserstein Fair Classification Ray Jiang Aldo Pacchiano T. Stepleton Heinrich Jiang Silvia Chiappa 80 181 0 28 Jul 2019
Counterfactual Reasoning for Fair Clinical Risk Prediction Stephen Pfohl Tony Duan D. Ding N. Shah OOD CML 71 58 0 14 Jul 2019
Rényi Fair Inference Sina Baharlouei Maher Nouiehed Ahmad Beirami Meisam Razaviyayn FaML 71 67 0 28 Jun 2019
FlipTest: Fairness Testing via Optimal Transport Emily Black Samuel Yeom Matt Fredrikson 162 96 0 21 Jun 2019
Adversarial training approach for local data debiasing Ulrich Aïvodji F. Bidet Sébastien Gambs Rosin Claude Ngueveu Alain Tapp 66 8 0 19 Jun 2019
Pairwise Fairness for Ranking and Regression Harikrishna Narasimhan Andrew Cotter Maya R. Gupta S. Wang 100 115 0 12 Jun 2019
Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patterns YooJung Choi G. Farnadi Behrouz Babaki Guy Van den Broeck FaML 80 27 0 10 Jun 2019
Maximum Weighted Loss Discrepancy Fereshte Khani Aditi Raghunathan Percy Liang 63 16 0 08 Jun 2019
Equalized odds postprocessing under imperfect group information Pranjal Awasthi Matthäus Kleindessner Jamie Morgenstern 92 91 0 07 Jun 2019
Flexibly Fair Representation Learning by Disentanglement Elliot Creager David Madras J. Jacobsen Marissa A. Weis Kevin Swersky T. Pitassi R. Zemel FaML OOD 201 334 0 06 Jun 2019
Optimized Score Transformation for Consistent Fair Classification Dennis L. Wei Karthikeyan N. Ramamurthy Flavio du Pin Calmon 54 16 0 31 May 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 171 485 0 28 May 2019
Compositional Fairness Constraints for Graph Embeddings A. Bose William L. Hamilton FaML 122 259 0 25 May 2019
An Algorithmic Framework for Fairness Elicitation Christopher Jung Michael Kearns Seth Neel Aaron Roth Logan Stapleton Zhiwei Steven Wu FedML FaML 69 56 0 25 May 2019