Avoiding Discrimination through Causal Reasoning

8 June 2017

Niki Kilbertus

Mateo Rojas-Carulla

Giambattista Parascandolo

Papers citing "Avoiding Discrimination through Causal Reasoning"

50 / 308 papers shown

Title
BeFair: Addressing Fairness in the Banking Sector Alessandro Castelnovo Riccardo Crupi Giulia Del Gamba Greta Greco A. Naseer D. Regoli Beatriz San Miguel González FaML 31 16 0 03 Feb 2021
Agent Incentives: A Causal Perspective Tom Everitt Ryan Carey Eric D. Langlois Pedro A. Ortega Shane Legg CML 11 53 0 02 Feb 2021
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification Maliha Tashfia Islam Anna Fariha A. Meliou Babak Salimi FaML 30 25 0 18 Jan 2021
Entropic Causal Inference: Identifiability and Finite Sample Results Spencer Compton Murat Kocaoglu Kristjan Greenewald Dmitriy A. Katz CML 17 17 0 10 Jan 2021
Outcome-Explorer: A Causality Guided Interactive Visual Interface for Interpretable Algorithmic Decision Making Md. Naimul Hoque Klaus Mueller CML 59 30 0 03 Jan 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 256 492 0 31 Dec 2020
Provably Training Overparameterized Neural Network Classifiers with Non-convex Constraints You-Lin Chen Zhaoran Wang Mladen Kolar 19 0 0 30 Dec 2020
Unbiased Subdata Selection for Fair Classification: A Unified Framework and Scalable Algorithms Qing Ye Weijun Xie FaML 24 13 0 22 Dec 2020
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately Fereshte Khani Percy Liang FaML 21 65 0 07 Dec 2020
FairBatch: Batch Selection for Model Fairness Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh VLM 16 128 0 03 Dec 2020
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder Hyemi Kim Seungjae Shin Joonho Jang Kyungwoo Song Weonyoung Joo Wanmo Kang Il-Chul Moon BDL CML 14 56 0 24 Nov 2020
Fairness-guided SMT-based Rectification of Decision Trees and Random Forests Jiang Zhang Ivan Beschastnikh Sergey Mechtaev Abhik Roychoudhury 9 8 0 22 Nov 2020
Shortcomings of Counterfactual Fairness and a Proposed Modification Fabian Beigang 14 0 0 14 Nov 2020
An example of prediction which complies with Demographic Parity and equalizes group-wise risks in the context of regression Evgenii Chzhen Nicolas Schreuder FaML 18 4 0 13 Nov 2020
Survey on Causal-based Machine Learning Fairness Notions K. Makhlouf Sami Zhioua C. Palamidessi FaML 19 84 0 19 Oct 2020
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 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
Fairness Constraints in Semi-supervised Learning Tao Zhang Tianqing Zhu Mengde Han Jing Li Wanlei Zhou Philip S. Yu FaML 8 7 0 14 Sep 2020
Improving Fair Predictions Using Variational Inference In Causal Models Rik Helwegen Christos Louizos Patrick Forré FaML 24 6 0 25 Aug 2020
The Fairness-Accuracy Pareto Front Susan Wei Marc Niethammer FaML 51 33 0 25 Aug 2020
Bias and Discrimination in AI: a cross-disciplinary perspective Xavier Ferrer Tom van Nuenen Jose Such Mark Coté Natalia Criado FaML 11 140 0 11 Aug 2020
Visual Analysis of Discrimination in Machine Learning Qianwen Wang Zhen Xu Zhutian Chen Yong Wang Shixia Liu Huamin Qu FaML 14 38 0 30 Jul 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
A Normative approach to Attest Digital Discrimination Natalia Criado Xavier Ferrer Aran Jose Such FaML 8 3 0 14 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
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 13 53 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
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
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
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
On Disentangled Representations Learned From Correlated Data Frederik Trauble Elliot Creager Niki Kilbertus Francesco Locatello Andrea Dittadi Anirudh Goyal Bernhard Schölkopf Stefan Bauer OOD CML 29 115 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
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Amir-Hossein Karimi Julius von Kügelgen Bernhard Schölkopf Isabel Valera CML 28 178 0 11 Jun 2020
A Variational Approach to Privacy and Fairness Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund FaML DRL 21 25 0 11 Jun 2020
Causal Feature Selection for Algorithmic Fairness Sainyam Galhotra Karthikeyan Shanmugam P. Sattigeri Kush R. Varshney FaML 28 39 0 10 Jun 2020
Achieving Equalized Odds by Resampling Sensitive Attributes Yaniv Romano Stephen Bates Emmanuel J. Candès FaML 18 48 0 08 Jun 2020
What's Sex Got To Do With Fair Machine Learning? Lily Hu Issa Kohler-Hausmann FaML 24 80 0 02 Jun 2020
AI Research Considerations for Human Existential Safety (ARCHES) Andrew Critch David M. Krueger 30 50 0 30 May 2020
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression Domagoj Cevid Loris Michel Jeffrey Näf N. Meinshausen Peter Buhlmann 35 39 0 29 May 2020