Auditing and Achieving Intersectional Fairness in Classification Problems

4 November 2019

Papers citing "Auditing and Achieving Intersectional Fairness in Classification Problems"

24 / 24 papers shown

Title
Intersectional Divergence: Measuring Fairness in Regression Joe Germino Nuno Moniz Nitesh V. Chawla FaML 63 0 0 01 May 2025
The Intersectionality Problem for Algorithmic Fairness Johannes Himmelreich Arbie Hsu Kristian Lum Ellen Veomett FaML 34 0 0 04 Nov 2024
Detecting Interpretable Subgroup Drifts F. Giobergia Eliana Pastor Luca de Alfaro Elena Baralis 16 0 0 26 Aug 2024
Auditing of AI: Legal, Ethical and Technical Approaches Jakob Mokander 44 37 0 07 Jul 2024
Synthetic Data Generation for Intersectional Fairness by Leveraging Hierarchical Group Structure Gaurav Maheshwari A. Bellet Pascal Denis Mikaela Keller 46 1 0 23 May 2024
Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals Hyewon Jeong Collin M. Stultz Marzyeh Ghassemi 17 4 0 09 Aug 2023
Fair Without Leveling Down: A New Intersectional Fairness Definition Gaurav Maheshwari A. Bellet Pascal Denis Mikaela Keller FaML 29 2 0 21 May 2023
A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges Usman Gohar Lu Cheng FaML 27 31 0 11 May 2023
Statistical Inference for Fairness Auditing John J. Cherian Emmanuel J. Candès MLAU 35 7 0 05 May 2023
Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity Joshua Gardner Renzhe Yu Quan Nguyen Christopher A. Brooks René F. Kizilcec FedML 38 14 0 01 May 2023
Intersectional Fairness: A Fractal Approach Giulio Filippi Sara Zannone Adriano Soares Koshiyama 6 1 0 24 Feb 2023
Bias Mitigation Framework for Intersectional Subgroups in Neural Networks Narine Kokhlikyan B. Alsallakh Fulton Wang Vivek Miglani Oliver Aobo Yang David Adkins 14 1 0 26 Dec 2022
An Efficient Framework for Monitoring Subgroup Performance of Machine Learning Systems Huong Ha 19 0 0 16 Dec 2022
Using Open-Ended Stressor Responses to Predict Depressive Symptoms across Demographics Carlos Alejandro Aguirre Mark Dredze Philip Resnik 11 0 0 15 Nov 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 31 159 0 14 Jul 2022
Fairness in Recommender Systems: Research Landscape and Future Directions Yashar Deldjoo Dietmar Jannach Alejandro Bellogín Alessandro Difonzo Dario Zanzonelli OffRL FaML 86 82 0 23 May 2022
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation Angelina Wang V. V. Ramaswamy Olga Russakovsky FaML 23 92 0 10 May 2022
Fairness-Aware Naive Bayes Classifier for Data with Multiple Sensitive Features Stelios Boulitsakis-Logothetis FaML 8 5 0 23 Feb 2022
Identifying Biased Subgroups in Ranking and Classification Eliana Pastor Luca de Alfaro Elena Baralis CML 16 11 0 17 Aug 2021
InfoFair: Information-Theoretic Intersectional Fairness Jian Kang Tiankai Xie Xintao Wu Ross Maciejewski Hanghang Tong FaML 8 19 0 24 May 2021
Multi-fairness under class-imbalance Arjun Roy Vasileios Iosifidis Eirini Ntoutsi FaML 6 6 0 27 Apr 2021
Fairness seen as Global Sensitivity Analysis Clément Bénesse Fabrice Gamboa Jean-Michel Loubes Thibaut Boissin 13 12 0 08 Mar 2021
Causal Multi-Level Fairness Vishwali Mhasawade R. Chunara 6 26 0 14 Oct 2020
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 673 0 17 Feb 2018