Inherent Tradeoffs in Learning Fair Representations

19 June 2019

Papers citing "Inherent Tradeoffs in Learning Fair Representations"

45 / 45 papers shown

Title
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models Ruta Binkyte Ivaxi Sheth Zhijing Jin Mohammad Havaei Bernhard Schölkopf Mario Fritz 134 0 0 28 Feb 2025
Fair Resource Allocation in Weakly Coupled Markov Decision Processes Xiaohui Tu Yossiri Adulyasak Nima Akbarzadeh Erick Delage 44 0 0 14 Nov 2024
Rethinking Fair Representation Learning for Performance-Sensitive Tasks Charles Jones Fabio De Sousa Ribeiro Mélanie Roschewitz Daniel Coelho De Castro Ben Glocker FaML OOD CML 146 1 0 05 Oct 2024
Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning Qi Qi Quanqi Hu Qihang Lin Tianbao Yang 37 1 0 09 Jun 2024
Is On-Device AI Broken and Exploitable? Assessing the Trust and Ethics in Small Language Models Kalyan Nakka Jimmy Dani Nitesh Saxena 45 1 0 08 Jun 2024
Removing Biases from Molecular Representations via Information Maximization Chenyu Wang Sharut Gupta Caroline Uhler Tommi Jaakkola 15 4 0 01 Dec 2023
Learning to Generate Equitable Text in Dialogue from Biased Training Data Anthony Sicilia Malihe Alikhani 47 15 0 10 Jul 2023
Fairness Improves Learning from Noisily Labeled Long-Tailed Data Jiaheng Wei Zhaowei Zhu Gang Niu Tongliang Liu Sijia Liu Masashi Sugiyama Yang Liu 36 6 0 22 Mar 2023
Fairness Increases Adversarial Vulnerability Cuong Tran Keyu Zhu Ferdinando Fioretto Pascal Van Hentenryck 31 6 0 21 Nov 2022
Fairness-aware Regression Robust to Adversarial Attacks Yulu Jin Lifeng Lai FaML OOD 29 4 0 04 Nov 2022
Fair Inference for Discrete Latent Variable Models Rashidul Islam Shimei Pan James R. Foulds FaML 43 1 0 15 Sep 2022
FedDAR: Federated Domain-Aware Representation Learning Aoxiao Zhong Hao He Zhaolin Ren Na Li Quanzheng Li OOD AI4CE 29 9 0 08 Sep 2022
To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontier Camille Olivia Little Michael Weylandt Genevera I. Allen 24 13 0 31 May 2022
Certifying Some Distributional Fairness with Subpopulation Decomposition Mintong Kang Linyi Li Maurice Weber Yang Liu Ce Zhang Bo-wen Li OOD 56 15 0 31 May 2022
Counterfactual Fairness with Partially Known Causal Graph Aoqi Zuo Susan Wei Tongliang Liu Bo Han Anton van den Hengel Biwei Huang OOD FaML 19 19 0 27 May 2022
Pruning has a disparate impact on model accuracy Cuong Tran Ferdinando Fioretto Jung-Eun Kim Rakshit Naidu 39 38 0 26 May 2022
Conditional Supervised Contrastive Learning for Fair Text Classification Jianfeng Chi Will Shand Yaodong Yu Kai-Wei Chang Han Zhao Yuan Tian FaML 46 14 0 23 May 2022
Survey on Fair Reinforcement Learning: Theory and Practice Pratik Gajane A. Saxena M. Tavakol George Fletcher Mykola Pechenizkiy FaML OffRL 35 13 0 20 May 2022
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning Natalie Dullerud Karsten Roth Kimia Hamidieh Nicolas Papernot Marzyeh Ghassemi 30 15 0 23 Mar 2022
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey Ferdinando Fioretto Cuong Tran Pascal Van Hentenryck Keyu Zhu FaML 24 60 0 16 Feb 2022
Learning Fair Representations via Rate-Distortion Maximization Somnath Basu Roy Chowdhury Snigdha Chaturvedi FaML 6 14 0 31 Jan 2022
There is an elephant in the room: Towards a critique on the use of fairness in biometrics Ana Valdivia Júlia Corbera Serrajòrdia Aneta Swianiewicz 21 14 0 16 Dec 2021
Group-Aware Threshold Adaptation for Fair Classification T. Jang P. Shi Xiaoqian Wang FaML 83 36 0 08 Nov 2021
Improving Fairness via Federated Learning Yuchen Zeng Hongxu Chen Kangwook Lee FedML 19 60 0 29 Oct 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
Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making Yi Yang Ying Nian Wu Mei Li Xiangyu Chang Yong Tan FaML 13 0 0 21 Sep 2021
Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search Jialu Wang Yang Liu Qing Guo FaML 157 95 0 12 Sep 2021
Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks Xudong Shen Yongkang Wong Mohan S. Kankanhalli FaML 37 20 0 01 Sep 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 32 159 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 38 16 0 24 Jun 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 27 51 0 16 Jun 2021
Fair Normalizing Flows Mislav Balunović Anian Ruoss Martin Vechev AAML 16 36 0 10 Jun 2021
Cooperative Multi-Agent Fairness and Equivariant Policies Niko A. Grupen B. Selman Daniel D. Lee FaML 11 11 0 10 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 27 47 0 04 Jun 2021
Representative & Fair Synthetic Data P. Tiwald Alexandra Ebert Daniel Soukup 21 12 0 07 Apr 2021
Understanding and Mitigating Accuracy Disparity in Regression Jianfeng Chi Yuan Tian Geoffrey J. Gordon Han Zhao 24 25 0 24 Feb 2021
Emergent Unfairness in Algorithmic Fairness-Accuracy Trade-Off Research A. Feder Cooper Ellen Abrams FaML 22 60 0 01 Feb 2021
Fairness in Machine Learning L. Oneto Silvia Chiappa FaML 256 488 0 31 Dec 2020
On Learning Language-Invariant Representations for Universal Machine Translation Hao Zhao Junjie Hu Andrej Risteski 40 11 0 11 Aug 2020
A Variational Approach to Privacy and Fairness Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund FaML DRL 19 25 0 11 Jun 2020
Disparate Vulnerability to Membership Inference Attacks B. Kulynych Mohammad Yaghini Giovanni Cherubin Michael Veale Carmela Troncoso 13 39 0 02 Jun 2019
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 674 0 17 Feb 2018
A statistical framework for fair predictive algorithms K. Lum J. Johndrow FaML 177 104 0 25 Oct 2016
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,084 0 24 Oct 2016
Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour M. Mohri Afshin Rostamizadeh 179 789 0 19 Feb 2009