Fair prediction with disparate impact: A study of bias in recidivism prediction instruments

24 October 2016

Papers citing "Fair prediction with disparate impact: A study of bias in recidivism prediction instruments"

50 / 858 papers shown

Title
Intra-Processing Methods for Debiasing Neural Networks Yash Savani Colin White G. NaveenSundar 61 44 0 15 Jun 2020
Towards Model-Agnostic Post-Hoc Adjustment for Balancing Ranking Fairness and Algorithm Utility Sen Cui Weishen Pan Changshui Zhang Fei Wang 67 14 0 15 Jun 2020
Fairness Under Feature Exemptions: Counterfactual and Observational Measures Sanghamitra Dutta Praveen Venkatesh Piotr (Peter) Mardziel Anupam Datta P. Grover 51 17 0 14 Jun 2020
Fair Influence Maximization: A Welfare Optimization Approach Aida Rahmattalabi S. Jabbari Himabindu Lakkaraju P. Vayanos Max Izenberg Ryan Brown Eric Rice Milind Tambe 57 51 0 14 Jun 2020
Fairness in Forecasting and Learning Linear Dynamical Systems Quan-Gen Zhou Jakub Mareˇcek Robert Shorten AI4TS 96 7 0 12 Jun 2020
Group-Fair Online Allocation in Continuous Time Semih Cayci Swati Gupta A. Eryilmaz FaML 63 20 0 11 Jun 2020
How Interpretable and Trustworthy are GAMs? C. Chang S. Tan Benjamin J. Lengerich Anna Goldenberg R. Caruana FAtt 127 80 0 11 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 23 4 0 11 Jun 2020
Hypergraph Clustering for Finding Diverse and Experienced Groups Ilya Amburg Nate Veldt Austin R. Benson 71 5 0 10 Jun 2020
Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability Sitan Chen Frederic Koehler Ankur Moitra Morris Yau 77 22 0 08 Jun 2020
Principles to Practices for Responsible AI: Closing the Gap Daniel S. Schiff B. Rakova A. Ayesh Anat Fanti M. Lennon 89 89 0 08 Jun 2020
Achieving Equalized Odds by Resampling Sensitive Attributes Yaniv Romano Stephen Bates Emmanuel J. Candès FaML 39 51 0 08 Jun 2020
Effects of algorithmic flagging on fairness: quasi-experimental evidence from Wikipedia Nathan TeBlunthuis Benjamin Mako Hill Aaron L Halfaker 21 15 0 04 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 69 40 0 26 May 2020
Sentiment Analysis: Automatically Detecting Valence, Emotions, and Other Affectual States from Text Saif M. Mohammad 70 315 0 25 May 2020
Projection to Fairness in Statistical Learning Thibaut Le Gouic Jean-Michel Loubes Philippe Rigollet 74 3 0 24 May 2020
Fair Classification via Unconstrained Optimization Ibrahim Alabdulmohsin FaML 47 6 0 21 May 2020
Principal Fairness for Human and Algorithmic Decision-Making Kosuke Imai Zhichao Jiang FaML 85 31 0 21 May 2020
Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy Bashir Rastegarpanah M. Crovella Krishna P. Gummadi FaML 46 8 0 19 May 2020
Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics Donald Martin Vinodkumar Prabhakaran Jill A. Kuhlberg A. Smart William S. Isaac FaML 80 63 0 15 May 2020
Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning Pieter Delobelle Paul Temple Gilles Perrouin Benoit Frénay P. Heymans Bettina Berendt AAML FaML 134 16 0 14 May 2020
Cyberbullying Detection with Fairness Constraints O. Gencoglu 91 49 0 09 May 2020
In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction Caroline Linjun Wang Bin Han Bhrij Patel Cynthia Rudin FaML HAI 105 88 0 08 May 2020
Ensuring Fairness under Prior Probability Shifts Arpita Biswas Suvam Mukherjee OOD 66 34 0 06 May 2020
Sample Complexity of Uniform Convergence for Multicalibration Eliran Shabat Lee Cohen Yishay Mansour FaML 75 28 0 04 May 2020
Dimensions of Diversity in Human Perceptions of Algorithmic Fairness Nina Grgic-Hlaca Gabriel Lima Adrian Weller Elissa M. Redmiles FaML 61 40 0 02 May 2020
Posterior Calibrated Training on Sentence Classification Tasks Taehee Jung Dongyeop Kang Hua Cheng L. Mentch Thomas Schaaf UQCV 40 12 0 29 Apr 2020
Demographics Should Not Be the Reason of Toxicity: Mitigating Discrimination in Text Classifications with Instance Weighting Guanhua Zhang Bing Bai Junqi Zhang Kun Bai Conghui Zhu Tiejun Zhao 103 71 0 29 Apr 2020
Learning a Formula of Interpretability to Learn Interpretable Formulas M. Virgolin A. D. Lorenzo Eric Medvet Francesca Randone 60 35 0 23 Apr 2020
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets Angelina Wang Alexander Liu Ryan Zhang Anat Kleiman Leslie Kim Dora Zhao Iroha Shirai Arvind Narayanan Olga Russakovsky 89 191 0 16 Apr 2020
Poisoning Attacks on Algorithmic Fairness David Solans Battista Biggio Carlos Castillo AAML 84 82 0 15 Apr 2020
Contrastive Examples for Addressing the Tyranny of the Majority V. Sharmanska Lisa Anne Hendricks Trevor Darrell Novi Quadrianto 72 29 0 14 Apr 2020
Individual Fairness in Pipelines Cynthia Dwork Christina Ilvento Meena Jagadeesan FaML 58 40 0 12 Apr 2020
FACT: A Diagnostic for Group Fairness Trade-offs Joon Sik Kim Jiahao Chen Ameet Talwalkar FaML 62 15 0 07 Apr 2020
Abstracting Fairness: Oracles, Metrics, and Interpretability Cynthia Dwork Christina Ilvento G. Rothblum Pragya Sur FaML 79 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 49 31 0 03 Apr 2020
Bias in Machine Learning -- What is it Good for? Thomas Hellström Virginia Dignum Suna Bensch AI4CE FaML 18 3 0 01 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
Covariance-Robust Dynamic Watermarking Matt Olfat S. Sloan P. Hespanhol Matthew Porter Ram Vasudevan A. Aswani AAML 52 9 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
Fairness by Explicability and Adversarial SHAP Learning James M. Hickey Pietro G. Di Stefano V. Vasileiou FAtt FedML 123 19 0 11 Mar 2020
Auditing ML Models for Individual Bias and Unfairness Songkai Xue Mikhail Yurochkin Yuekai Sun MLAU 106 23 0 11 Mar 2020
Addressing multiple metrics of group fairness in data-driven decision making M. Miron Songül Tolan Emilia Gómez Carlos Castillo FaML 109 8 0 10 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 98 221 0 09 Mar 2020
Demographic Bias in Biometrics: A Survey on an Emerging Challenge P. Drozdowski Christian Rathgeb A. Dantcheva N. Damer C. Busch FaML 198 206 0 05 Mar 2020
Counterfactual fairness: removing direct effects through regularization Pietro G. Di Stefano James M. Hickey V. Vasileiou FaML 128 19 0 25 Feb 2020
Bandit Learning with Delayed Impact of Actions Wei Tang Chien-Ju Ho Yang Liu 112 12 0 24 Feb 2020
Fair Adversarial Networks G. Cevora 38 4 0 23 Feb 2020
Fair Prediction with Endogenous Behavior Christopher Jung Sampath Kannan Changhwa Lee Mallesh M. Pai Aaron Roth R. Vohra FaML 50 38 0 18 Feb 2020
A Possibility in Algorithmic Fairness: Can Calibration and Equal Error Rates Be Reconciled? Claire Lazar Reich Suhas Vijaykumar FaML 67 19 0 18 Feb 2020