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Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints

29 June 2018

Papers citing "Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints"

37 / 37 papers shown

Title
Near-Optimal Solutions of Constrained Learning Problems Juan Elenter Luiz F. O. Chamon Alejandro Ribeiro 65 6 0 18 Mar 2024
Specification Overfitting in Artificial Intelligence Benjamin Roth Pedro Henrique Luz de Araujo Yuxi Xia Saskia Kaltenbrunner Christoph Korab 227 1 0 13 Mar 2024
Explanation-Guided Fair Federated Learning for Transparent 6G RAN Slicing Swastika Roy Hatim Chergui C. Verikoukis FedML 58 3 0 18 Jul 2023
Towards clinical AI fairness: A translational perspective Mingxuan Liu Yilin Ning Salinelat Teixayavong M. Mertens Jie Xu ... Ravi Chandran Narrendar Fei Wang Leo Anthony Celi M. Ong Nan Liu FaML 59 0 0 26 Apr 2023
Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees Songkai Xue Yuekai Sun Mikhail Yurochkin FaML 59 0 0 15 Jan 2023
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data Harsh Rangwani Sumukh K Aithal Mayank Mishra R. Venkatesh Babu 75 31 0 28 Dec 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 105 177 0 14 Jul 2022
Active Learning with Safety Constraints Romain Camilleri Andrew Wagenmaker Jamie Morgenstern Lalit P. Jain Kevin Jamieson 66 14 0 22 Jun 2022
A Sociotechnical View of Algorithmic Fairness Mateusz Dolata Stefan Feuerriegel Gerhard Schwabe FaML 76 100 0 27 Sep 2021
Evaluating Debiasing Techniques for Intersectional Biases Shivashankar Subramanian Xudong Han Timothy Baldwin Trevor Cohn Lea Frermann 157 50 0 21 Sep 2021
Measuring Generalization with Optimal Transport Ching-Yao Chuang Youssef Mroueh Kristjan Greenewald Antonio Torralba Stefanie Jegelka OT 90 27 0 07 Jun 2021
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning Yuyan Wang Xuezhi Wang Alex Beutel Flavien Prost Jilin Chen Ed H. Chi FaML 61 48 0 04 Jun 2021
An Empirical Framework for Domain Generalization in Clinical Settings Haoran Zhang Natalie Dullerud Laleh Seyyed-Kalantari Q. Morris Shalmali Joshi Marzyeh Ghassemi OOD AI4CE 125 61 0 20 Mar 2021
Fair Mixup: Fairness via Interpolation Ching-Yao Chuang Youssef Mroueh 79 140 0 11 Mar 2021
Constrained Learning with Non-Convex Losses Luiz F. O. Chamon Santiago Paternain Miguel Calvo-Fullana Alejandro Ribeiro 91 38 0 08 Mar 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 309 500 0 31 Dec 2020
Does enforcing fairness mitigate biases caused by subpopulation shift? Subha Maity Debarghya Mukherjee Mikhail Yurochkin Yuekai Sun 151 24 0 06 Nov 2020
Debiasing classifiers: is reality at variance with expectation? Ashrya Agrawal Florian Pfisterer B. Bischl Francois Buet-Golfouse Srijan Sood Jiahao Chen Sameena Shah Sebastian J. Vollmer CML FaML 36 18 0 04 Nov 2020
Deep F-measure Maximization for End-to-End Speech Understanding Leda Sari M. Hasegawa-Johnson FedML 21 0 0 08 Aug 2020
An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction Stephen Pfohl Agata Foryciarz N. Shah FaML 116 113 0 20 Jul 2020
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data Yishay Mansour M. Mohri Jae Hun Ro A. Suresh Ke Wu 113 28 0 19 Jul 2020
Fairness with Overlapping Groups Forest Yang Moustapha Cissé Oluwasanmi Koyejo FaML 61 22 0 24 Jun 2020
Competitive Mirror Descent F. Schafer Anima Anandkumar H. Owhadi 66 13 0 17 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 64 40 0 26 May 2020
Ensuring Fairness under Prior Probability Shifts Arpita Biswas Suvam Mukherjee OOD 61 34 0 06 May 2020
Fair Learning with Private Demographic Data Hussein Mozannar Mesrob I. Ohannessian Nathan Srebro 90 76 0 26 Feb 2020
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 85 79 0 24 Feb 2020
Lagrangian Duality for Constrained Deep Learning Ferdinando Fioretto Pascal Van Hentenryck Terrence W.K. Mak Cuong Tran Federico Baldo M. Lombardi PINN 61 84 0 26 Jan 2020
Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems Xuezhi Wang Nithum Thain Anu Sinha Flavien Prost Ed H. Chi Jilin Chen Alex Beutel FaML CoGe 27 1 0 05 Nov 2019
Pairwise Fairness for Ranking and Regression Harikrishna Narasimhan Andrew Cotter Maya R. Gupta S. Wang 89 115 0 12 Jun 2019
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil FaML 222 87 0 12 Jun 2019
Fairness for Robust Log Loss Classification Ashkan Rezaei Rizal Fathony Omid Memarrast Brian Ziebart FaML 58 8 0 10 Mar 2019
Noise-tolerant fair classification A. Lamy Ziyuan Zhong A. Menon Nakul Verma NoLa 96 77 0 30 Jan 2019
Identifying and Correcting Label Bias in Machine Learning Heinrich Jiang Ofir Nachum FaML 104 284 0 15 Jan 2019
Uniform Convergence of Gradients for Non-Convex Learning and Optimization Dylan J. Foster Ayush Sekhari Karthik Sridharan 82 68 0 25 Oct 2018
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals Andrew Cotter Heinrich Jiang S. Wang Taman Narayan Maya R. Gupta Seungil You Karthik Sridharan 90 158 0 11 Sep 2018
Two-Player Games for Efficient Non-Convex Constrained Optimization Andrew Cotter Heinrich Jiang Karthik Sridharan 99 118 0 17 Apr 2018