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Inherent Tradeoffs in Learning Fair Representations

Neural Information Processing Systems (NeurIPS), 2019

19 June 2019

Papers citing "Inherent Tradeoffs in Learning Fair Representations"

39 / 139 papers shown

Title
Improving Fairness via Federated Learning Yuchen Zeng Hongxu Chen Kangwook Lee FedML 312 73 0 29 Oct 2021
Algorithm Fairness in AI for Medicine and Healthcare Richard J. Chen Tiffany Y. Chen Jana Lipkova Judy J. Wang Drew F. K. Williamson Ming Y. Lu S. Sahai Faisal Mahmood FaML 274 53 0 01 Oct 2021
A Sociotechnical View of Algorithmic FairnessInformation Systems Journal (ISJ), 2021 Mateusz Dolata Stefan Feuerriegel Gerhard Schwabe FaML 187 116 0 27 Sep 2021
Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values Haewon Jeong Hao Wang Flavio du Pin Calmon FaML 194 45 0 21 Sep 2021
Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making Yi Yang Ying Nian Wu Mei Li Xiangyu Chang Yong Tan FaML 223 0 0 21 Sep 2021
Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search Jialu Wang Yang Liu Xinze Wang FaML 270 112 0 12 Sep 2021
On Characterizing the Trade-off in Invariant Representation Learning Bashir Sadeghi Sepehr Dehdashtian Vishnu Boddeti 199 11 0 08 Sep 2021
F3: Fair and Federated Face Attribute Classification with Heterogeneous DataPacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2021 Samhita Kanaparthy Manisha Padala Sankarshan Damle Ravi Kiran Sarvadevabhatla Sujit Gujar CVBM 178 3 0 06 Sep 2021
Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown TasksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 Xudong Shen Yongkang Wong Mohan S. Kankanhalli FaML 217 24 0 01 Sep 2021
FADE: FAir Double Ensemble Learning for Observable and Counterfactual OutcomesConference on Fairness, Accountability and Transparency (FAccT), 2021 Alan Mishler Edward H. Kennedy FaML 159 24 0 01 Sep 2021
Equity-Directed Bootstrapping: Examples and Analysis Harish S. Bhat Majerle Reeves S. Goldman-Mellor 105 0 0 14 Aug 2021
Statistical Guarantees for Fairness Aware Plug-In Algorithms Drona Khurana S. Ravichandran Sparsh Jain N. Edakunni FaML 173 0 0 27 Jul 2021
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning Paul Pu Liang Yiwei Lyu Xiang Fan Zetian Wu Yun Cheng ... Peter Wu Michelle A. Lee Yuke Zhu Ruslan Salakhutdinov Louis-Philippe Morency VLM 211 220 0 15 Jul 2021
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data Paul Pu Liang Terrance Liu Anna Cai Michal Muszynski Ryo Ishii Nicholas B. Allen Randy P. Auerbach David Brent Ruslan Salakhutdinov Louis-Philippe Morency 205 18 0 24 Jun 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 198 63 0 16 Jun 2021
Costs and Benefits of Fair Regression Han Zhao FaML 101 10 0 16 Jun 2021
Fair Normalizing FlowsInternational Conference on Learning Representations (ICLR), 2021 Mislav Balunović Anian Ruoss Martin Vechev AAML 234 46 0 10 Jun 2021
Cooperative Multi-Agent Fairness and Equivariant PoliciesAAAI Conference on Artificial Intelligence (AAAI), 2021 Niko A. Grupen B. Selman Daniel D. Lee FaML 135 13 0 10 Jun 2021
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task LearningKnowledge Discovery and Data Mining (KDD), 2021 Yuyan Wang Xuezhi Wang Alex Beutel Flavien Prost Jilin Chen Ed H. Chi FaML 138 57 0 04 Jun 2021
Robust Fairness-aware Learning Under Sample Selection Bias Wei Du Xintao Wu FaML OOD 103 14 0 24 May 2021
Causally motivated Shortcut Removal Using Auxiliary LabelsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 Maggie Makar Ben Packer D. Moldovan Davis W. Blalock Yoni Halpern Alexander DÁmour OOD CML 225 82 0 13 May 2021
Mitigating Political Bias in Language Models Through Reinforced CalibrationAAAI Conference on Artificial Intelligence (AAAI), 2021 Ruibo Liu Chenyan Jia Jason W. Wei Guangxuan Xu Lili Wang Soroush Vosoughi 131 109 0 30 Apr 2021
Representative & Fair Synthetic Data P. Tiwald Alexandra Ebert Daniel Soukup 155 12 0 07 Apr 2021
Understanding and Mitigating Accuracy Disparity in RegressionInternational Conference on Machine Learning (ICML), 2021 Jianfeng Chi Yuan Tian Geoffrey J. Gordon Han Zhao 179 28 0 24 Feb 2021
Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial ProblemNeural Information Processing Systems (NeurIPS), 2021 Adarsh Barik Jean Honorio FaML 152 7 0 19 Feb 2021
Emergent Unfairness in Algorithmic Fairness-Accuracy Trade-Off ResearchAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021 A. Feder Cooper Ellen Abrams FaML 401 69 0 01 Feb 2021
Fundamental Limits and Tradeoffs in Invariant Representation LearningJournal of machine learning research (JMLR), 2020 Han Zhao Chen Dan Bryon Aragam Tommi Jaakkola Geoffrey J. Gordon Pradeep Ravikumar FaML 477 53 0 19 Dec 2020
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately Fereshte Khani Abigail Z. Jacobs FaML 202 70 0 07 Dec 2020
Fairness Constraints in Semi-supervised Learning Tao Zhang Tianqing Zhu Mengde Han Jing Li Wanlei Zhou Philip S. Yu FaML 157 8 0 14 Sep 2020
On Learning Language-Invariant Representations for Universal Machine TranslationInternational Conference on Machine Learning (ICML), 2020 Hao Zhao Junjie Hu Andrej Risteski 180 8 0 11 Aug 2020
Towards Accuracy-Fairness Paradox: Adversarial Example-based Data Augmentation for Visual DebiasingACM Multimedia (ACM MM), 2020 Yi Zhang Jitao Sang 176 59 0 27 Jul 2020
Fairness constraints can help exact inference in structured prediction Kevin Bello Jean Honorio 134 6 0 01 Jul 2020
FACT: A Diagnostic for Group Fairness Trade-offsInternational Conference on Machine Learning (ICML), 2020 Joon Sik Kim Jiahao Chen Ameet Talwalkar FaML 166 15 0 07 Apr 2020
To Split or Not to Split: The Impact of Disparate Treatment in ClassificationIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020 Hao Wang Hsiang Hsu Mario Díaz Flavio du Pin Calmon 355 24 0 12 Feb 2020
Think Locally, Act Globally: Federated Learning with Local and Global Representations Paul Pu Liang Terrance Liu Liu Ziyin Nicholas B. Allen Randy P. Auerbach David Brent Ruslan Salakhutdinov Louis-Philippe Morency FedML 547 665 0 06 Jan 2020
Kernel Dependence Regularizers and Gaussian Processes with Applications to Algorithmic FairnessPattern Recognition (Pattern Recognit.), 2019 Zhu Li Adrián Pérez-Suay Gustau Camps-Valls Dino Sejdinovic FaML 170 23 0 11 Nov 2019
Conditional Learning of Fair RepresentationsInternational Conference on Learning Representations (ICLR), 2019 Han Zhao Amanda Coston T. Adel Geoffrey J. Gordon FaML 236 124 0 16 Oct 2019
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation Han Zhao Jianfeng Chi Yuan Tian Geoffrey J. Gordon MIACV 168 2 0 19 Jun 2019
Disparate Vulnerability to Membership Inference AttacksProceedings on Privacy Enhancing Technologies (PoPETs), 2019 B. Kulynych Mohammad Yaghini Giovanni Cherubin Michael Veale Carmela Troncoso 466 49 0 02 Jun 2019