Learning Adversarially Fair and Transferable Representations

17 February 2018

Papers citing "Learning Adversarially Fair and Transferable Representations"

50 / 103 papers shown

Title
Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability Metrics Insung Kong Kunwoong Kim Yongdai Kim FaML 25 1 0 09 May 2025
ReLU integral probability metric and its applications Yuha Park Kunwoong Kim Insung Kong Yongdai Kim 34 0 0 26 Apr 2025
FAIR-SIGHT: Fairness Assurance in Image Recognition via Simultaneous Conformal Thresholding and Dynamic Output Repair Arya Fayyazi M. Kamal Massoud Pedram 26 0 0 10 Apr 2025
FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee Puheng Li James Y. Zou Linjun Zhang FaML 77 4 0 13 Mar 2025
Differential Adjusted Parity for Learning Fair Representations Bucher Sahyouni Matthew Vowels Liqun Chen Simon Hadfield FaML 84 0 0 13 Feb 2025
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 127 1 0 05 Oct 2024
Efficient Fairness-Performance Pareto Front Computation Mark Kozdoba Binyamin Perets Shie Mannor 21 0 0 26 Sep 2024
Multi-Output Distributional Fairness via Post-Processing Gang Li Qihang Lin Ayush Ghosh Tianbao Yang 49 0 0 31 Aug 2024
Building Socially-Equitable Public Models Yejia Liu Jianyi Yang Pengfei Li Tongxin Li Shaolei Ren OffRL 38 0 0 04 Jun 2024
Initial Exploration of Zero-Shot Privacy Utility Tradeoffs in Tabular Data Using GPT-4 Bishwas Mandal G. Amariucai Shuangqing Wei 24 1 0 07 Apr 2024
A Comprehensive Review of Machine Learning Advances on Data Change: A Cross-Field Perspective Jeng-Lin Li Chih-Fan Hsu Ming-Ching Chang Wei-Chao Chen OOD 36 2 0 20 Feb 2024
Generalized People Diversity: Learning a Human Perception-Aligned Diversity Representation for People Images Hansa Srinivasan Candice Schumann Aradhana Sinha David Madras Gbolahan O. Olanubi Alex Beutel Susanna Ricco Jilin Chen 20 5 0 25 Jan 2024
Counterfactual Fairness for Predictions using Generative Adversarial Networks Yuchen Ma Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel 26 2 0 26 Oct 2023
Elucidate Gender Fairness in Singing Voice Transcription Xiangming Gu Weizhen Zeng Ye Wang 10 3 0 05 Aug 2023
No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging Charles Jones Daniel Coelho De Castro Fabio De Sousa Ribeiro Ozan Oktay Melissa McCradden Ben Glocker FaML CML 30 9 0 31 Jul 2023
Learning to Generate Equitable Text in Dialogue from Biased Training Data Anthony Sicilia Malihe Alikhani 38 15 0 10 Jul 2023
To be Robust and to be Fair: Aligning Fairness with Robustness Junyi Chai Xiaoqian Wang 33 2 0 31 Mar 2023
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification Tianci Liu Haoyu Wang Yaqing Wang Xiaoqian Wang Lu Su Jing Gao 24 6 0 19 Feb 2023
Provable Detection of Propagating Sampling Bias in Prediction Models Pavan Ravishankar Qingyu Mo E. McFowland Daniel B. Neill 27 3 0 13 Feb 2023
Debiasing Vision-Language Models via Biased Prompts Ching-Yao Chuang Varun Jampani Yuanzhen Li Antonio Torralba Stefanie Jegelka VLM 28 96 0 31 Jan 2023
MMD-B-Fair: Learning Fair Representations with Statistical Testing Namrata Deka Danica J. Sutherland 11 6 0 15 Nov 2022
Okapi: Generalising Better by Making Statistical Matches Match Myles Bartlett Sara Romiti V. Sharmanska Novi Quadrianto 32 3 0 07 Nov 2022
Fairness-aware Regression Robust to Adversarial Attacks Yulu Jin Lifeng Lai FaML OOD 16 4 0 04 Nov 2022
On Learning Fairness and Accuracy on Multiple Subgroups Changjian Shui Gezheng Xu Qi Chen Jiaqi Li Charles X. Ling Tal Arbel Boyu Wang Christian Gagné 37 37 0 19 Oct 2022
Information Removal at the bottleneck in Deep Neural Networks Enzo Tartaglione 41 2 0 30 Sep 2022
Fairness and robustness in anti-causal prediction Maggie Makar Alexander DÁmour OOD 29 10 0 20 Sep 2022
Fair Inference for Discrete Latent Variable Models Rashidul Islam Shimei Pan James R. Foulds FaML 30 1 0 15 Sep 2022
Disentangled Representation with Causal Constraints for Counterfactual Fairness Ziqi Xu Jixue Liu Debo Cheng Jiuyong Li Lin Liu Ke Wang FaML OOD CML 30 7 0 19 Aug 2022
Open Long-Tailed Recognition in a Dynamic World Ziwei Liu Zhongqi Miao Xiaohang Zhan Jiayun Wang Boqing Gong Stella X. Yu VLM 23 18 0 17 Aug 2022
Invariant Representations with Stochastically Quantized Neural Networks Mattia Cerrato Marius Köppel Roberto Esposito Stefan Kramer MQ 17 4 0 04 Aug 2022
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts Haotao Wang Junyuan Hong Jiayu Zhou Zhangyang Wang OOD 43 11 0 04 Jul 2022
FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning Tao Qi Fangzhao Wu Chuhan Wu Lingjuan Lyu Tongye Xu Zhongliang Yang Yongfeng Huang Xing Xie FedML 24 36 0 07 Jun 2022
Conditional Supervised Contrastive Learning for Fair Text Classification Jianfeng Chi Will Shand Yaodong Yu Kai-Wei Chang Han Zhao Yuan Tian FaML 41 14 0 23 May 2022
De-biasing "bias" measurement K. Lum Yunfeng Zhang Amanda Bower 11 26 0 11 May 2022
Don't Throw it Away! The Utility of Unlabeled Data in Fair Decision Making Miriam Rateike Ayan Majumdar Olga Mineeva Krishna P. Gummadi Isabel Valera OffRL 28 11 0 10 May 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 25 77 0 06 May 2022
Optimising Equal Opportunity Fairness in Model Training Aili Shen Xudong Han Trevor Cohn Timothy Baldwin Lea Frermann FaML 16 28 0 05 May 2022
SoFaiR: Single Shot Fair Representation Learning Xavier Gitiaux Huzefa Rangwala 21 4 0 26 Apr 2022
Unsupervised Learning of Unbiased Visual Representations C. Barbano Enzo Tartaglione Marco Grangetto SSL CML OOD 16 1 0 26 Apr 2022
You Are What You Write: Preserving Privacy in the Era of Large Language Models Richard Plant V. Giuffrida Dimitra Gkatzia PILM 15 19 0 20 Apr 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 14 15 0 23 Mar 2022
Improving the Fairness of Chest X-ray Classifiers Haoran Zhang Natalie Dullerud Karsten Roth Lauren Oakden-Rayner Stephen R. Pfohl Marzyeh Ghassemi 21 65 0 23 Mar 2022
Attainability and Optimality: The Equalized Odds Fairness Revisited Zeyu Tang Kun Zhang FaML 6 11 0 24 Feb 2022
SLIDE: a surrogate fairness constraint to ensure fairness consistency Kunwoong Kim Ilsang Ohn Sara Kim Yongdai Kim 24 4 0 07 Feb 2022
Learning fair representation with a parametric integral probability metric Dongha Kim Kunwoong Kim Insung Kong Ilsang Ohn Yongdai Kim FaML 17 16 0 07 Feb 2022
Controlling Directions Orthogonal to a Classifier Yilun Xu Hao He T. Shen Tommi Jaakkola 61 19 0 27 Jan 2022
Disentanglement and Generalization Under Correlation Shifts Christina M. Funke Paul Vicol Kuan-Chieh Jackson Wang Matthias Kümmerer R. Zemel Matthias Bethge OOD 31 7 0 29 Dec 2021
Towards Principled Disentanglement for Domain Generalization Hanlin Zhang Yi-Fan Zhang Weiyang Liu Adrian Weller Bernhard Schölkopf Eric P. Xing OOD 23 112 0 27 Nov 2021
Latent Space Smoothing for Individually Fair Representations Momchil Peychev Anian Ruoss Mislav Balunović Maximilian Baader Martin Vechev FaML 30 18 0 26 Nov 2021
Group-Aware Threshold Adaptation for Fair Classification T. Jang P. Shi Xiaoqian Wang FaML 78 36 0 08 Nov 2021