Empirical Risk Minimization under Fairness Constraints

23 February 2018

Papers citing "Empirical Risk Minimization under Fairness Constraints"

48 / 98 papers shown

Title
Consider the Alternatives: Navigating Fairness-Accuracy Tradeoffs via Disqualification G. Rothblum G. Yona FaML 33 1 0 02 Oct 2021
Fairness guarantee in multi-class classification Christophe Denis Romuald Elie Mohamed Hebiri Franccois Hu FaML 48 48 0 28 Sep 2021
Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values Haewon Jeong Hao Wang Flavio du Pin Calmon FaML 51 33 0 21 Sep 2021
Improving Fairness for Data Valuation in Horizontal Federated Learning Zhenan Fan Huang Fang Zirui Zhou Jian Pei M. Friedlander Changxin Liu Yong Zhang TDI FedML 45 47 0 19 Sep 2021
Achieving Model Fairness in Vertical Federated Learning Changxin Liu Zhenan Fan Zirui Zhou Yang Shi J. Pei Lingyang Chu Yong Zhang FedML 60 12 0 17 Sep 2021
Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud Michaela Hardt Xiaoguang Chen Xiaoyi Cheng Michele Donini J. Gelman ... Muhammad Bilal Zafar Sanjiv Ranjan Das Kevin Haas Tyler Hill K. Kenthapadi ELM FaML 36 42 0 07 Sep 2021
Unsupervised Learning of Debiased Representations with Pseudo-Attributes Seonguk Seo Joon-Young Lee Bohyung Han FaML 76 48 0 06 Aug 2021
Constrained Classification and Policy Learning T. Kitagawa Shosei Sakaguchi A. Tetenov OffRL 37 12 0 24 Jun 2021
Multi-objective Asynchronous Successive Halving Robin Schmucker Michele Donini Muhammad Bilal Zafar David Salinas Cédric Archambeau 32 24 0 23 Jun 2021
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis Zihang Meng Rudrasis Chakraborty Vikas Singh 9 9 0 08 Jun 2021
Label-Imbalanced and Group-Sensitive Classification under Overparameterization Ganesh Ramachandra Kini Orestis Paraskevas Samet Oymak Christos Thrampoulidis 36 94 0 02 Mar 2021
Learning Invariant Representations using Inverse Contrastive Loss A. K. Akash Vishnu Suresh Lokhande Sathya Ravi Vikas Singh SSL 21 8 0 16 Feb 2021
Technical Challenges for Training Fair Neural Networks Valeriia Cherepanova V. Nanda Micah Goldblum John P. Dickerson Tom Goldstein FaML 25 22 0 12 Feb 2021
Fairness through Social Welfare Optimization V. Chen J. N. Hooker 24 1 0 30 Jan 2021
Characterizing Fairness Over the Set of Good Models Under Selective Labels Amanda Coston Ashesh Rambachan Alexandra Chouldechova FaML 32 82 0 02 Jan 2021
Towards Fair Deep Anomaly Detection Hongjing Zhang Ian Davidson FaML 55 39 0 29 Dec 2020
On the Privacy Risks of Algorithmic Fairness Hong Chang Reza Shokri FaML 38 110 0 07 Nov 2020
Coping with Label Shift via Distributionally Robust Optimisation J.N. Zhang A. Menon Andreas Veit Srinadh Bhojanapalli Sanjiv Kumar S. Sra OOD 24 70 0 23 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
MARS: Mixed Virtual and Real Wearable Sensors for Human Activity Recognition with Multi-Domain Deep Learning Model Ling Pei Songpengcheng Xia Lei Chu Fanyi Xiao Qi Wu Wenxian Yu Zixuan Zhang 37 30 0 20 Sep 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 28 61 0 18 Jul 2020
Learning Bounds for Risk-sensitive Learning Jaeho Lee Sejun Park Jinwoo Shin 25 46 0 15 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
Probably Approximately Correct Constrained Learning Luiz F. O. Chamon Alejandro Ribeiro 22 38 0 09 Jun 2020
Fair Bayesian Optimization Valerio Perrone Michele Donini Muhammad Bilal Zafar Robin Schmucker K. Kenthapadi Cédric Archambeau FaML 27 84 0 09 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 15 39 0 26 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 49 371 0 30 Apr 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 908 0 02 Mar 2020
Robust Optimization for Fairness with Noisy Protected Groups S. Wang Wenshuo Guo Harikrishna Narasimhan Andrew Cotter Maya R. Gupta Michael I. Jordan NoLa 27 118 0 21 Feb 2020
Fair Data Adaptation with Quantile Preservation Drago Plečko N. Meinshausen 14 30 0 15 Nov 2019
Efficient Fair Principal Component Analysis Mohammad Mahdi Kamani Farzin Haddadpour R. Forsati M. Mahdavi 13 36 0 12 Nov 2019
Fairness Violations and Mitigation under Covariate Shift Harvineet Singh Rina Singh Vishwali Mhasawade R. Chunara OOD 27 15 0 02 Nov 2019
Wasserstein Fair Classification Ray Jiang Aldo Pacchiano T. Stepleton Heinrich Jiang Silvia Chiappa 33 173 0 28 Jul 2019
Rényi Fair Inference Sina Baharlouei Maher Nouiehed Ahmad Beirami Meisam Razaviyayn FaML 24 66 0 28 Jun 2019
Learning Fair Representations for Kernel Models Zilong Tan Samuel Yeom Matt Fredrikson Ameet Talwalkar FaML 35 25 0 27 Jun 2019
Learning Fair and Transferable Representations L. Oneto Michele Donini Andreas Maurer Massimiliano Pontil FaML 37 19 0 25 Jun 2019
Variational Fair Clustering Imtiaz Masud Ziko Eric Granger Jing Yuan Ismail Ben Ayed 30 13 0 19 Jun 2019
Pairwise Fairness for Ranking and Regression Harikrishna Narasimhan Andrew Cotter Maya R. Gupta S. Wang 33 112 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 24 85 0 12 Jun 2019
Testing DNN Image Classifiers for Confusion & Bias Errors Yuchi Tian Ziyuan Zhong Vicente Ordonez Gail E. Kaiser Baishakhi Ray 24 52 0 20 May 2019
Fair Classification and Social Welfare Lily Hu Yiling Chen FaML 26 88 0 01 May 2019
Fairness risk measures Robert C. Williamson A. Menon FaML 33 135 0 24 Jan 2019
Fair k-Center Clustering for Data Summarization Matthäus Kleindessner Pranjal Awasthi Jamie Morgenstern 42 162 0 24 Jan 2019
Identifying and Correcting Label Bias in Machine Learning Heinrich Jiang Ofir Nachum FaML 16 281 0 15 Jan 2019
Eliminating Latent Discrimination: Train Then Mask Soheil Ghili Ehsan Kazemi Amin Karbasi FaML 27 9 0 12 Nov 2018
A General Framework for Fair Regression Jack K. Fitzsimons AbdulRahman Al Ali Michael A. Osborne Stephen J. Roberts FaML 27 37 0 10 Oct 2018
A statistical framework for fair predictive algorithms K. Lum J. Johndrow FaML 179 105 0 25 Oct 2016