Counterfactual Fairness

20 March 2017

Papers citing "Counterfactual Fairness"

50 / 823 papers shown

Title
Causal Multi-Level Fairness Vishwali Mhasawade R. Chunara 30 26 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
On the Fairness of Causal Algorithmic Recourse Julius von Kügelgen Amir-Hossein Karimi Umang Bhatt Isabel Valera Adrian Weller Bernhard Schölkopf FaML 80 82 0 13 Oct 2020
Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness Jessie Finocchiaro R. Maio F. Monachou Gourab K. Patro Manish Raghavan Ana-Andreea Stoica Stratis Tsirtsis FaML 26 56 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
Assessing Classifier Fairness with Collider Bias Zhenlong Xu Ziqi Xu Jixue Liu Debo Cheng Jiuyong Li Lin Liu Adelaide Canada Ziqi Xu Zhenlong Xu contributed equally to this paper CML FaML 20 4 0 08 Oct 2020
Fairness Perception from a Network-Centric Perspective Farzan Masrour P. Tan A. Esfahanian FaML 19 2 0 07 Oct 2020
How and Why to Use Experimental Data to Evaluate Methods for Observational Causal Inference A. Gentzel Purva Pruthi David D. Jensen CML 24 18 0 06 Oct 2020
Can we Generalize and Distribute Private Representation Learning? Sheikh Shams Azam Taejin Kim Seyyedali Hosseinalipour Carlee Joe-Wong S. Bagchi Christopher G. Brinton 44 10 0 05 Oct 2020
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 37 616 0 04 Oct 2020
Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce Discrimination Tao Zhang Tianqing Zhu Jing Li Mengde Han Wanlei Zhou Philip S. Yu FaML 37 49 0 25 Sep 2020
SSCR: Iterative Language-Based Image Editing via Self-Supervised Counterfactual Reasoning Tsu-Jui Fu Xinze Wang Scott T. Grafton Miguel P. Eckstein William Yang Wang 39 40 0 21 Sep 2020
Group Fairness by Probabilistic Modeling with Latent Fair Decisions YooJung Choi Meihua Dang Guy Van den Broeck FaML 16 30 0 18 Sep 2020
Principles and Practice of Explainable Machine Learning Vaishak Belle I. Papantonis FaML 24 437 0 18 Sep 2020
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals Saloni Dash V. Balasubramanian Amit Sharma CML 27 65 0 17 Sep 2020
FairFace Challenge at ECCV 2020: Analyzing Bias in Face Recognition Tomás Sixta Julio C. S. Jacques Junior Pau Buch-Cardona Neil M. Robertson E. Vazquez Sergio Escalera CVBM 35 34 0 16 Sep 2020
Justicia: A Stochastic SAT Approach to Formally Verify Fairness Bishwamittra Ghosh D. Basu Kuldeep S. Meel 27 36 0 14 Sep 2020
Fairness Constraints in Semi-supervised Learning Tao Zhang Tianqing Zhu Mengde Han Jing Li Wanlei Zhou Philip S. Yu FaML 6 7 0 14 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 46 62 0 11 Sep 2020
A Framework for Fairer Machine Learning in Organizations Lily Morse M. Teodorescu Yazeed Awwad Gerald C. Kane FaML FedML 27 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
Adversarial Learning for Counterfactual Fairness Vincent Grari Sylvain Lamprier Marcin Detyniecki FaML 25 22 0 30 Aug 2020
How to "Improve" Prediction Using Behavior Modification Galit Shmueli A. Tafti OffRL AI4TS 11 8 0 26 Aug 2020
Improving Fair Predictions Using Variational Inference In Causal Models Rik Helwegen Christos Louizos Patrick Forré FaML 21 6 0 25 Aug 2020
The Fairness-Accuracy Pareto Front Susan Wei Marc Niethammer FaML 51 33 0 25 Aug 2020
Beyond Individual and Group Fairness Pranjal Awasthi Corinna Cortes Yishay Mansour M. Mohri FaML 23 22 0 21 Aug 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
A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution A. Khademi Vasant Honavar CML 20 9 0 01 Aug 2020
Visual Analysis of Discrimination in Machine Learning Qianwen Wang Zhen Xu Zhutian Chen Yong Wang Shixia Liu Huamin Qu FaML 12 38 0 30 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
Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context Ehsan Toreini Mhairi Aitken Kovila P. L. Coopamootoo Karen Elliott Vladimiro González-Zelaya P. Missier Magdalene Ng Aad van Moorsel 39 17 0 17 Jul 2020
Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design Shusen Liu B. Kailkhura Jize Zhang A. Hiszpanski Emily Robertson Donald Loveland T. Y. Han 20 2 0 16 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
The Impossibility Theorem of Machine Fairness -- A Causal Perspective Kailash Karthik FaML 20 24 0 12 Jul 2020
Algorithmic Fairness in Education René F. Kizilcec Hansol Lee FaML 38 120 0 10 Jul 2020
Machine learning fairness notions: Bridging the gap with real-world applications K. Makhlouf Sami Zhioua C. Palamidessi FaML 11 53 0 30 Jun 2020
Actionable Attribution Maps for Scientific Machine Learning Shusen Liu B. Kailkhura Jize Zhang A. Hiszpanski Emily Robertson Donald Loveland T. Y. Han 14 1 0 30 Jun 2020
Generative causal explanations of black-box classifiers Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 35 73 0 24 Jun 2020
Verifying Individual Fairness in Machine Learning Models Philips George John Deepak Vijaykeerthy Diptikalyan Saha FaML 27 57 0 21 Jun 2020
Achieving Fairness via Post-Processing in Web-Scale Recommender Systems Preetam Nandy Cyrus DiCiccio Divya Venugopalan Heloise Logan Kinjal Basu N. Karoui FaML 21 30 0 19 Jun 2020
Algorithmic Decision Making with Conditional Fairness Renzhe Xu Peng Cui Kun Kuang Bo Li Linjun Zhou Zheyan Shen Wei Cui FaML 23 36 0 18 Jun 2020
Individual Calibration with Randomized Forecasting Shengjia Zhao Tengyu Ma Stefano Ermon 16 57 0 18 Jun 2020
Causal intersectionality for fair ranking Ke Yang Joshua R. Loftus Julia Stoyanovich 35 40 0 15 Jun 2020
On Adversarial Bias and the Robustness of Fair Machine Learning Hong Chang Ta Duy Nguyen S. K. Murakonda Ehsan Kazemi Reza Shokri FaML OOD FedML 16 50 0 15 Jun 2020
Intra-Processing Methods for Debiasing Neural Networks Yash Savani Colin White G. NaveenSundar 16 43 0 15 Jun 2020
Causal Inference with Deep Causal Graphs Álvaro Parafita Jordi Vitrià CML 14 10 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
Fairness in Forecasting and Learning Linear Dynamical Systems Quan-Gen Zhou Jakub Mareˇcek Robert Shorten AI4TS 37 7 0 12 Jun 2020
Fair Regression with Wasserstein Barycenters Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil 32 101 0 12 Jun 2020
Getting a CLUE: A Method for Explaining Uncertainty Estimates Javier Antorán Umang Bhatt T. Adel Adrian Weller José Miguel Hernández-Lobato UQCV BDL 50 112 0 11 Jun 2020