Papers citing 'Avoiding Discrimination through Causal Reasoning'

Title
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness Adam Foster Árpi Vezér C. A. Glastonbury Páidí Creed Sam Abujudeh Aaron Sim FaML 169 7 0 15 Jun 2021
Information Theoretic Measures for Fairness-aware Feature Selection S. Khodadadian M. Nafea AmirEmad Ghassami Negar Kiyavash 111 8 0 01 Jun 2021
A Clarification of the Nuances in the Fairness Metrics LandscapeScientific Reports (Sci Rep), 2021 Alessandro Castelnovo Riccardo Crupi Greta Greco D. Regoli Ilaria Giuseppina Penco A. Cosentini FaML 363 228 0 01 Jun 2021
Measuring Model Fairness under Noisy Covariates: A Theoretical PerspectiveAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021 Flavien Prost Pranjal Awasthi Nicholas Blumm A. Kumthekar Trevor Potter Li Wei Xuezhi Wang Ed H. Chi Jilin Chen Alex Beutel 166 16 0 20 May 2021
Personalized Counterfactual Fairness in RecommendationAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021 Yunqi Li Hanxiong Chen Shuyuan Xu Yingqiang Ge Zelong Li FaML OffRL 219 162 0 20 May 2021
Equity and Artificial Intelligence in Education: Will "AIEd" Amplify or Alleviate Inequities in Education? Kenneth Holstein Shayan Doroudi 111 54 0 27 Apr 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals Sainyam Galhotra Romila Pradhan Babak Salimi CML 214 117 0 22 Mar 2021
Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems Chloé Bakalar Renata Barreto Stevie Bergman Miranda Bogen Bobbie Chern ... J. Simons Jonathan Tannen Edmund Tong Kate Vredenburgh Jiejing Zhao FaML 193 29 0 10 Mar 2021
Fairness seen as Global Sensitivity AnalysisMachine-mediated learning (ML), 2021 Clément Bénesse Fabrice Gamboa Jean-Michel Loubes Thibaut Boissin 172 18 0 08 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and ApplicationsInformation Fusion (Inf. Fusion), 2021 Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 315 213 0 07 Mar 2021
Towards Causal Representation Learning Bernhard Schölkopf Francesco Locatello Stefan Bauer Nan Rosemary Ke Nal Kalchbrenner Anirudh Goyal Yoshua Bengio OOD CML AI4CE 276 339 0 22 Feb 2021
Disentangled Representations from Non-Disentangled Models Valentin Khrulkov L. Mirvakhabova Ivan Oseledets Artem Babenko OCL DRL CoGe 85 17 0 11 Feb 2021
A Ranking Approach to Fair Classification Jakob Schoeffer Niklas Kuehl Isabel Valera FaML 128 7 0 08 Feb 2021
Removing biased data to improve fairness and accuracy Sahil Verma Michael Ernst René Just FaML 212 28 0 05 Feb 2021
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 108 19 0 03 Feb 2021
Agent Incentives: A Causal PerspectiveAAAI Conference on Artificial Intelligence (AAAI), 2021 Tom Everitt Ryan Carey Eric D. Langlois Pedro A. Ortega Shane Legg CML 248 62 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 239 30 0 18 Jan 2021
Entropic Causal Inference: Identifiability and Finite Sample ResultsNeural Information Processing Systems (NeurIPS), 2021 Spencer Compton Murat Kocaoglu Kristjan Greenewald Dmitriy A. Katz CML 173 20 0 10 Jan 2021
Outcome-Explorer: A Causality Guided Interactive Visual Interface for Interpretable Algorithmic Decision MakingIEEE Transactions on Visualization and Computer Graphics (TVCG), 2021 Md. Naimul Hoque Klaus Mueller CML 314 36 0 03 Jan 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 592 533 0 31 Dec 2020
Provably Training Overparameterized Neural Network Classifiers with Non-convex ConstraintsElectronic Journal of Statistics (EJS), 2020 You-Lin Chen Zhaoran Wang Mladen Kolar 165 0 0 30 Dec 2020
Unbiased Subdata Selection for Fair Classification: A Unified Framework and Scalable Algorithms Qing Ye Weijun Xie FaML 117 13 0 22 Dec 2020
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately Fereshte Khani Abigail Z. Jacobs FaML 198 70 0 07 Dec 2020
FairBatch: Batch Selection for Model FairnessInternational Conference on Learning Representations (ICLR), 2020 Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh VLM 333 143 0 03 Dec 2020
Counterfactual Fairness with Disentangled Causal Effect Variational AutoencoderAAAI Conference on Artificial Intelligence (AAAI), 2020 Hyemi Kim Seungjae Shin Joonho Jang Kyungwoo Song Weonyoung Joo Wanmo Kang Il-Chul Moon BDL CML 230 64 0 24 Nov 2020
Fairness-guided SMT-based Rectification of Decision Trees and Random Forests Jiang Zhang Ivan Beschastnikh Sergey Mechtaev Abhik Roychoudhury 86 8 0 22 Nov 2020
Shortcomings of Counterfactual Fairness and a Proposed Modification Fabian Beigang 86 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 147 4 0 13 Nov 2020
Survey on Causal-based Machine Learning Fairness Notions K. Makhlouf Sami Zhioua C. Palamidessi FaML 410 98 0 19 Oct 2020
Causal Multi-Level Fairness Vishwali Mhasawade R. Chunara 171 29 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 103 11 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 553 91 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 272 63 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 110 22 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 118 6 0 08 Oct 2020
Fairness in Machine Learning: A SurveyACM Computing Surveys (ACM CSUR), 2020 Simon Caton C. Haas FaML 469 782 0 04 Oct 2020
Fairness in Semi-supervised Learning: Unlabeled Data Help to Reduce DiscriminationIEEE Transactions on Knowledge and Data Engineering (TKDE), 2020 Tao Zhang Tianqing Zhu Jing Li Mengde Han Wanlei Zhou Philip S. Yu FaML 143 56 0 25 Sep 2020
Fairness Constraints in Semi-supervised Learning Tao Zhang Tianqing Zhu Mengde Han Jing Li Wanlei Zhou Philip S. Yu FaML 153 8 0 14 Sep 2020
Improving Fair Predictions Using Variational Inference In Causal Models Rik Helwegen Christos Louizos Patrick Forré FaML 149 6 0 25 Aug 2020
The Fairness-Accuracy Pareto Front Susan Wei Marc Niethammer FaML 197 36 0 25 Aug 2020
Bias and Discrimination in AI: a cross-disciplinary perspectiveIEEE technology & society magazine (TS), 2020 Xavier Ferrer Tom van Nuenen Jose Such Mark Coté Natalia Criado FaML 132 191 0 11 Aug 2020
Visual Analysis of Discrimination in Machine LearningIEEE Transactions on Visualization and Computer Graphics (TVCG), 2020 Qianwen Wang Zhen Xu Zhutian Chen Yong Wang Shixia Liu Huamin Qu FaML 217 48 0 30 Jul 2020
Distributionally Robust Losses for Latent Covariate MixturesOperational Research (OR), 2020 John C. Duchi Tatsunori Hashimoto Hongseok Namkoong 164 87 0 28 Jul 2020
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction Stephen Pfohl Agata Foryciarz N. Shah FaML 373 130 0 20 Jul 2020
A Normative approach to Attest Digital Discrimination Natalia Criado Xavier Ferrer Aran Jose Such FaML 155 3 0 14 Jul 2020
Ensuring Fairness Beyond the Training DataNeural Information Processing Systems (NeurIPS), 2020 Debmalya Mandal Samuel Deng Suman Jana Jeannette M. Wing Daniel J. Hsu FaML OOD 169 62 0 12 Jul 2020
Algorithmic Fairness in Education René F. Kizilcec Hansol Lee FaML 239 158 0 10 Jul 2020
Machine learning fairness notions: Bridging the gap with real-world applications K. Makhlouf Sami Zhioua C. Palamidessi FaML 185 62 0 30 Jun 2020
Generative causal explanations of black-box classifiersNeural Information Processing Systems (NeurIPS), 2020 Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 245 76 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 240 36 0 18 Jun 2020

Contrastive Mixture of Posteriors for Counterfactual Inference, Data
Integration and Fairness

169

7

0

15 Jun 2021

Information Theoretic Measures for Fairness-aware Feature Selection

111

8

0

01 Jun 2021

A Clarification of the Nuances in the Fairness Metrics LandscapeScientific Reports (Sci Rep), 2021

Alessandro Castelnovo

Riccardo Crupi

Greta Greco

D. Regoli

Ilaria Giuseppina Penco

A. Cosentini

FaML

363

228

0

01 Jun 2021

Measuring Model Fairness under Noisy Covariates: A Theoretical PerspectiveAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021

166

16

0

20 May 2021

Personalized Counterfactual Fairness in RecommendationAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021

219

162

0

20 May 2021