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Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation

11 January 2021

Papers citing "Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation"

35 / 35 papers shown

Title
Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving Regularization Ziyu Gong Jim Lim David I. Inouye DiffM 31 0 0 17 Jun 2025
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective Firas Laakom Haobo Chen Jürgen Schmidhuber Yuheng Bu 14 0 0 09 Jun 2025
Improving Recommendation Fairness without Sensitive Attributes Using Multi-Persona LLMs Haoran Xin Ying Sun Chao Wang Yanke Yu Weijia Zhang Hui Xiong FaML 39 0 0 26 May 2025
Fair Representation Learning for Continuous Sensitive Attributes using Expectation of Integral Probability Metrics Insung Kong Kunwoong Kim Yongdai Kim FaML 184 1 0 09 May 2025
ReLU integral probability metric and its applications Yuha Park Kunwoong Kim Insung Kong Yongdai Kim 93 0 0 26 Apr 2025
Fair Sufficient Representation Learning Xueyu Zhou Chun Yin IP Jian Huang FaML 72 0 0 29 Mar 2025
Fair Text Classification via Transferable Representations Thibaud Leteno Michael Perrot Charlotte Laclau Antoine Gourru Christophe Gravier FaML 117 0 0 10 Mar 2025
Bridging Fairness Gaps: A (Conditional) Distance Covariance Perspective in Fairness Learning Ruifan Huang Haixia Liu FedML FaML 168 1 0 01 Dec 2024
Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning Qi Qi Quanqi Hu Qihang Lin Tianbao Yang 126 1 0 09 Jun 2024
Back to the Drawing Board for Fair Representation Learning Angeline Pouget Nikola Jovanović Mark Vero Robin Staab Martin Vechev 57 0 0 28 May 2024
DispaRisk: Auditing Fairness Through Usable Information Jonathan Vasquez Carlotta Domeniconi Huzefa Rangwala 61 0 0 20 May 2024
From Discrete to Continuous: Deep Fair Clustering With Transferable Representations Xiang Zhang 90 0 0 24 Mar 2024
From Principle to Practice: Vertical Data Minimization for Machine Learning Robin Staab Nikola Jovanović Mislav Balunović Martin Vechev 76 7 0 17 Nov 2023
Towards Practical Non-Adversarial Distribution Matching Ziyu Gong Ben Usman Han Zhao David I. Inouye OOD 57 2 0 30 Oct 2023
Learning Fair Representations with High-Confidence Guarantees Yuhong Luo Austin Hoag Philip S Thomas FaML AI4TS 195 1 0 23 Oct 2023
A Novel Information-Theoretic Objective to Disentangle Representations for Fair Classification Pierre Colombo Nathan Noiry Guillaume Staerman Pablo Piantanida FaML DRL 78 1 0 21 Oct 2023
Towards Poisoning Fair Representations Tianci Liu Haoyu Wang Feijie Wu Hengtong Zhang Pan Li Lu Su Jing Gao AAML 69 2 0 28 Sep 2023
FAIRER: Fairness as Decision Rationale Alignment Tianlin Li Qing Guo Aishan Liu Mengnan Du Zhiming Li Yang Liu 60 16 0 27 Jun 2023
FairDP: Certified Fairness with Differential Privacy K. Tran Ferdinando Fioretto Issa M. Khalil My T. Thai Nhathai Phan 76 0 0 25 May 2023
Model and Evaluation: Towards Fairness in Multilingual Text Classification Nankai Lin Junheng He Zhenghang Tang Dong-ping Zhou Aimin Yang 90 2 0 28 Mar 2023
Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play J. Liu Krishnamurthy Dvijotham Jihyeon Janel Lee Quan Yuan Martin Strobel Balaji Lakshminarayanan Deepak Ramachandran 75 5 0 11 Feb 2023
Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness A. Zayed Prasanna Parthasarathi Gonçalo Mordido Hamid Palangi Samira Shabanian Sarath Chandar 54 22 0 20 Nov 2022
MMD-B-Fair: Learning Fair Representations with Statistical Testing Namrata Deka Danica J. Sutherland 98 7 0 15 Nov 2022
FARE: Provably Fair Representation Learning with Practical Certificates Nikola Jovanović Mislav Balunović Dimitar I. Dimitrov Martin Vechev 210 13 0 13 Oct 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
Understanding Instance-Level Impact of Fairness Constraints Jialu Wang Xinze Wang Yang Liu TDI FaML 108 34 0 30 Jun 2022
Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing Jiayin Jin Zeru Zhang Yang Zhou Lingfei Wu 71 13 0 22 Jun 2022
Fair Representation Learning through Implicit Path Alignment Changjian Shui Qi Chen Jiaqi Li Boyu Wang Christian Gagné 103 28 0 26 May 2022
SoFaiR: Single Shot Fair Representation Learning Xavier Gitiaux Huzefa Rangwala 73 4 0 26 Apr 2022
Distraction is All You Need for Fairness Mehdi Yazdani-Jahromi Amirarsalan Rajabi Ali Khodabandeh Yalabadi Aida Tayebi O. Garibay 113 3 0 15 Mar 2022
Attributing Fair Decisions with Attention Interventions Ninareh Mehrabi Umang Gupta Fred Morstatter Greg Ver Steeg Aram Galstyan 68 21 0 08 Sep 2021
Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE Junya Chen Zhe Gan Xuan Li Qing Guo Liqun Chen ... Belinda Zeng Wenlian Lu Fan Li Lawrence Carin Chenyang Tao 96 28 0 02 Jul 2021
Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization Qing Guo Junya Chen Dong Wang Yuewei Yang Xinwei Deng Lawrence Carin Fan Li Jing-Zheng Huang Chenyang Tao 83 21 0 02 Jul 2021
Fair Normalizing Flows Mislav Balunović Anian Ruoss Martin Vechev AAML 57 38 0 10 Jun 2021
Conditional Contrastive Learning for Improving Fairness in Self-Supervised Learning Martin Q. Ma Yao-Hung Hubert Tsai Paul Pu Liang Han Zhao Kun Zhang Ruslan Salakhutdinov Louis-Philippe Morency SSL 83 16 0 05 Jun 2021