Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

14 November 2017

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

50 / 443 papers shown

Title
Minimax Pareto Fairness: A Multi Objective Perspective Natalia Martínez Martín Bertrán Guillermo Sapiro FaML 25 190 0 03 Nov 2020
Fair Classification with Group-Dependent Label Noise Jialu Wang Yang Liu Caleb C. Levy NoLa 16 101 0 31 Oct 2020
One-vs.-One Mitigation of Intersectional Bias: A General Method to Extend Fairness-Aware Binary Classification Kenji Kobayashi Yuri Nakao FaML 30 8 0 26 Oct 2020
Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberation Hong Shen Wesley Hanwen Deng Aditi Chattopadhyay Zhiwei Steven Wu Xu Wang Haiyi Zhu 27 63 0 22 Oct 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 19 373 0 14 Oct 2020
Equitable Allocation of Healthcare Resources with Fair Cox Models Kamrun Naher Keya Rashidul Islam Shimei Pan I. Stockwell James R. Foulds 14 9 0 14 Oct 2020
Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings Vinith Suriyakumar Nicolas Papernot Anna Goldenberg Marzyeh Ghassemi OOD 36 64 0 13 Oct 2020
Large-Scale Methods for Distributionally Robust Optimization Daniel Levy Y. Carmon John C. Duchi Aaron Sidford 39 205 0 12 Oct 2020
Metrics and methods for a systematic comparison of fairness-aware machine learning algorithms Gareth Jones James M. Hickey Pietro G. Di Stefano C. Dhanjal Laura C. Stoddart V. Vasileiou FaML 33 21 0 08 Oct 2020
The Short Anthropological Guide to the Study of Ethical AI Alexandrine Royer SyDa 16 0 0 07 Oct 2020
Fairness Perception from a Network-Centric Perspective Farzan Masrour P. Tan A. Esfahanian FaML 21 2 0 07 Oct 2020
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 37 616 0 04 Oct 2020
Group Fairness by Probabilistic Modeling with Latent Fair Decisions YooJung Choi Meihua Dang Guy Van den Broeck FaML 18 30 0 18 Sep 2020
A Framework for Fairer Machine Learning in Organizations Lily Morse M. Teodorescu Yazeed Awwad Gerald C. Kane FaML FedML 29 5 0 10 Sep 2020
On the Identification of Fair Auditors to Evaluate Recommender Systems based on a Novel Non-Comparative Fairness Notion Mukund Telukunta Venkata Sriram Siddhardh Nadendla FaML 16 0 0 09 Sep 2020
"And the Winner Is...": Dynamic Lotteries for Multi-group Fairness-Aware Recommendation Nasim Sonboli Robin Burke Nicholas Mattei Farzad Eskandanian Tian Gao FaML 10 12 0 05 Sep 2020
Fairness in the Eyes of the Data: Certifying Machine-Learning Models Shahar Segal Yossi Adi Benny Pinkas Carsten Baum C. Ganesh Joseph Keshet FedML 19 34 0 03 Sep 2020
Adversarial Learning for Counterfactual Fairness Vincent Grari Sylvain Lamprier Marcin Detyniecki FaML 25 22 0 30 Aug 2020
Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Conformal Prediction Sets R. Berk Arun K. Kuchibhotla 13 5 0 26 Aug 2020
Beyond Individual and Group Fairness Pranjal Awasthi Corinna Cortes Yishay Mansour M. Mohri FaML 25 22 0 21 Aug 2020
Moment Multicalibration for Uncertainty Estimation Christopher Jung Changhwa Lee Mallesh M. Pai Aaron Roth R. Vohra UQCV 12 64 0 18 Aug 2020
Deep F-measure Maximization for End-to-End Speech Understanding Leda Sari M. Hasegawa-Johnson FedML 4 0 0 08 Aug 2020
Distributionally Robust Losses for Latent Covariate Mixtures John C. Duchi Tatsunori Hashimoto Hongseok Namkoong 18 79 0 28 Jul 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
Towards causal benchmarking of bias in face analysis algorithms Guha Balakrishnan Yuanjun Xiong Wei Xia Pietro Perona CVBM 29 90 0 13 Jul 2020
Ensuring Fairness Beyond the Training Data Debmalya Mandal Samuel Deng Suman Jana Jeannette M. Wing Daniel J. Hsu FaML OOD 27 58 0 12 Jul 2020
New Oracle-Efficient Algorithms for Private Synthetic Data Release G. Vietri Grace Tian Mark Bun Thomas Steinke Zhiwei Steven Wu SyDa 88 75 0 10 Jul 2020
Machine learning fairness notions: Bridging the gap with real-world applications K. Makhlouf Sami Zhioua C. Palamidessi FaML 13 53 0 30 Jun 2020
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness Mikhail Yurochkin Yuekai Sun FaML 25 49 0 25 Jun 2020
Fairness with Overlapping Groups Forest Yang Moustapha Cissé Oluwasanmi Koyejo FaML 16 21 0 24 Jun 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 30 329 0 23 Jun 2020
Fair Performance Metric Elicitation Gaurush Hiranandani Harikrishna Narasimhan Oluwasanmi Koyejo 32 18 0 23 Jun 2020
Distributional Individual Fairness in Clustering Nihesh Anderson S. Bera Syamantak Das Yang Liu FedML FaML 23 20 0 22 Jun 2020
How fair can we go in machine learning? Assessing the boundaries of fairness in decision trees Ana Valdivia Javier Sánchez-Monedero J. Casillas FaML 37 46 0 22 Jun 2020
Individual Calibration with Randomized Forecasting Shengjia Zhao Tengyu Ma Stefano Ermon 16 57 0 18 Jun 2020
LimeOut: An Ensemble Approach To Improve Process Fairness Vaishnavi Bhargava Miguel Couceiro A. Napoli FaML 23 20 0 17 Jun 2020
Learning Smooth and Fair Representations Xavier Gitiaux Huzefa Rangwala FaML 37 15 0 15 Jun 2020
Causal intersectionality for fair ranking Ke Yang Joshua R. Loftus Julia Stoyanovich 35 40 0 15 Jun 2020
Fairness Under Feature Exemptions: Counterfactual and Observational Measures Sanghamitra Dutta Praveen Venkatesh Piotr (Peter) Mardziel Anupam Datta P. Grover 14 16 0 14 Jun 2020
Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective Optimization G. D. Pelegrina Renan D. B. Brotto L. Duarte R. Attux João Marcos Travassos Romano 13 3 0 11 Jun 2020
Probably Approximately Correct Constrained Learning Luiz F. O. Chamon Alejandro Ribeiro 22 38 0 09 Jun 2020
Fair Bayesian Optimization Valerio Perrone Michele Donini Muhammad Bilal Zafar Robin Schmucker K. Kenthapadi Cédric Archambeau FaML 27 84 0 09 Jun 2020
A Notion of Individual Fairness for Clustering Matthäus Kleindessner Pranjal Awasthi Jamie Morgenstern FaML 40 30 0 08 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 15 39 0 26 May 2020
Opportunistic Multi-aspect Fairness through Personalized Re-ranking Nasim Sonboli Farzad Eskandanian Robin Burke Weiwen Liu B. Mobasher FaML 9 45 0 21 May 2020
Sample Complexity of Uniform Convergence for Multicalibration Eliran Shabat Lee Cohen Yishay Mansour FaML 21 26 0 04 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 52 371 0 30 Apr 2020
Genetic programming approaches to learning fair classifiers William La Cava J. Moore FaML 19 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 34 6 0 26 Apr 2020
Individual Fairness in Pipelines Cynthia Dwork Christina Ilvento Meena Jagadeesan FaML 22 40 0 12 Apr 2020