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Fair Classification with Group-Dependent Label Noise

31 October 2020

Yang Liu

Papers citing "Fair Classification with Group-Dependent Label Noise"

50 / 62 papers shown

Title
GFLC: Graph-based Fairness-aware Label Correction for Fair Classification Modar Sulaiman Kallol Roy 45 0 0 18 Jun 2025
Adaptive Bounded Exploration and Intermediate Actions for Data Debiasing Yifan Yang Yang Liu Parinaz Naghizadeh 114 1 0 10 Apr 2025
U-Fair: Uncertainty-based Multimodal Multitask Learning for Fairer Depression Detection Jiaee Cheong Aditya Bangar Sinan Kalkan Hatice Gunes 145 4 0 17 Jan 2025
The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning Jake Fawkes Nic Fishman Mel Andrews Zachary C. Lipton 109 1 0 12 Oct 2024
Fair-OBNC: Correcting Label Noise for Fairer Datasets Ines Oliveira e Silva Sérgio Jesus Hugo Ferreira Pedro Saleiro Inês Sousa P. Bizarro Carlos Soares 71 1 0 08 Oct 2024
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation Amartya Sanyal Yaxi Hu Yaodong Yu Yian Ma Yixin Wang Bernhard Schölkopf OODD 83 2 0 27 Jun 2024
From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions Trenton Chang Jenna Wiens 97 0 0 27 Jun 2024
Fairness Without Harm: An Influence-Guided Active Sampling Approach Jinlong Pang Jialu Wang Zhaowei Zhu Yuanshun Yao Chen Qian Yang Liu TDI 76 5 0 20 Feb 2024
Understanding Domain Generalization: A Noise Robustness Perspective Rui Qiao K. H. Low OOD 88 6 0 26 Jan 2024
Uncertainty-based Fairness Measures Selim Kuzucu Jiaee Cheong Hatice Gunes Sinan Kalkan UD PER 98 8 0 18 Dec 2023
How Far Can Fairness Constraints Help Recover From Biased Data? Mohit Sharma Amit Deshpande FaML 120 2 0 16 Dec 2023
Mitigating Label Bias in Machine Learning: Fairness through Confident Learning Yixuan Zhang Boyu Li Zenan Ling Feng Zhou FaML 45 5 0 14 Dec 2023
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models Zhaowei Zhu Jialu Wang Hao Cheng Yang Liu 99 20 0 19 Nov 2023
Post-hoc Bias Scoring Is Optimal For Fair Classification Wenlong Chen Yegor Klochkov Yang Liu FaML 91 8 0 09 Oct 2023
Quantifying and mitigating the impact of label errors on model disparity metrics Julius Adebayo Melissa Hall Bowen Yu Bobbie Chern 74 11 0 04 Oct 2023
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools Maximilian Schambach Rakshit Naidu Rayid Ghani Kit T. Rodolfa Daniel E. Ho Hoda Heidari FaML 89 17 0 29 Sep 2023
Leveraging an Alignment Set in Tackling Instance-Dependent Label Noise Donna Tjandra Jenna Wiens NoLa 52 4 0 10 Jul 2023
On the Cause of Unfairness: A Training Sample Perspective Yuanshun Yao Yang Liu TDI 77 0 0 30 Jun 2023
Systematic analysis of the impact of label noise correction on ML Fairness I. O. E. Silva Carlos Soares I. Sousa R. Ghani 39 2 0 28 Jun 2023
Sampling Individually-Fair Rankings that are Always Group Fair Sruthi Gorantla Anay Mehrotra Amit Deshpande Anand Louis FedML FaML 62 4 0 21 Jun 2023
AQuA: A Benchmarking Tool for Label Quality Assessment Mononito Goswami Vedant Sanil Arjun Choudhry Arvind Srinivasan Chalisa Udompanyawit Artur Dubrawski 104 13 0 15 Jun 2023
Mitigating Source Bias for Fairer Weak Supervision Changho Shin Sonia Cromp Dyah Adila Frederic Sala 73 2 0 30 Mar 2023
Fairness Improves Learning from Noisily Labeled Long-Tailed Data Jiaheng Wei Zhaowei Zhu Gang Niu Tongliang Liu Sijia Liu Masashi Sugiyama Yang Liu 68 7 0 22 Mar 2023
Counterfactual Prediction Under Outcome Measurement Error Luke M. Guerdan Amanda Coston Kenneth Holstein Zhiwei Steven Wu 90 15 0 22 Feb 2023
On (assessing) the fairness of risk score models Eike Petersen M. Ganz Sune Holm Aasa Feragen FaML 67 21 0 17 Feb 2023
Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making Luke M. Guerdan Amanda Coston Zhiwei Steven Wu Kenneth Holstein CML 82 30 0 13 Feb 2023
On Comparing Fair Classifiers under Data Bias Mohit Sharma Amit Deshpande R. Shah 96 2 0 12 Feb 2023
Ethical Considerations for Responsible Data Curation Jerone T. A. Andrews Dora Zhao William Thong Apostolos Modas Orestis Papakyriakopoulos Alice Xiang 158 22 0 07 Feb 2023
Fairness and Sequential Decision Making: Limits, Lessons, and Opportunities Samer B. Nashed Justin Svegliato Su Lin Blodgett FaML 58 6 0 13 Jan 2023
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data Minghong Fang Jia-Wei Liu Michinari Momma Yi Sun 71 4 0 13 Dec 2022
Fair Ranking with Noisy Protected Attributes Anay Mehrotra Nisheeth K. Vishnoi 89 19 0 30 Nov 2022
Learning with Noisy Labels over Imbalanced Subpopulations Mingcai Chen Yu Zhao Bing He Zongbo Han Bingzhe Wu Jianhua Yao 76 9 0 16 Nov 2022
A Survey on Preserving Fairness Guarantees in Changing Environments Ainhize Barrainkua Paula Gordaliza Jose A. Lozano Novi Quadrianto FaML 83 3 0 14 Nov 2022
Towards Fair Classification against Poisoning Attacks Han Xu Xiaorui Liu Yuxuan Wan Jiliang Tang 81 2 0 18 Oct 2022
Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes Zhaowei Zhu Yuanshun Yao Jiankai Sun Hanguang Li Yang Liu 98 24 0 06 Oct 2022
Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning Trenton Chang Michael Sjoding Jenna Wiens 83 11 0 01 Aug 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 113 177 0 14 Jul 2022
Understanding Unfairness in Fraud Detection through Model and Data Bias Interactions José P. Pombal André F. Cruz Joao Bravo Pedro Saleiro Mário A. T. Figueiredo P. Bizarro FaML 63 8 0 13 Jul 2022
Understanding Instance-Level Impact of Fairness Constraints Jialu Wang Xinze Wang Yang Liu TDI FaML 108 34 0 30 Jun 2022
Prisoners of Their Own Devices: How Models Induce Data Bias in Performative Prediction José P. Pombal Pedro Saleiro Mário A. T. Figueiredo P. Bizarro 61 4 0 27 Jun 2022
Social Bias Meets Data Bias: The Impacts of Labeling and Measurement Errors on Fairness Criteria Yiqiao Liao Parinaz Naghizadeh Ardabili 86 9 0 31 May 2022
A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms Nil-Jana Akpinar Manish Nagireddy Logan Stapleton H. Cheng Haiyi Zhu Steven Wu Hoda Heidari 110 15 0 21 Apr 2022
Identifiability of Label Noise Transition Matrix Yang Liu Hao Cheng Kun Zhang NoLa 101 49 0 04 Feb 2022
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features Zhaowei Zhu Jialu Wang Yang Liu NoLa 97 37 0 02 Feb 2022
Interpretable Data-Based Explanations for Fairness Debugging Romila Pradhan Jiongli Zhu Boris Glavic Babak Salimi 93 58 0 17 Dec 2021
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective Steven Euijong Whang Yuji Roh Hwanjun Song Jae-Gil Lee 83 352 0 13 Dec 2021
Adaptive Data Debiasing through Bounded Exploration Yifan Yang Yang Liu Parinaz Naghizadeh FaML 88 7 0 25 Oct 2021
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations Jiaheng Wei Zhaowei Zhu Weiran Wang Tongliang Liu Gang Niu Yang Liu NoLa 147 262 0 22 Oct 2021
Detecting Corrupted Labels Without Training a Model to Predict Zhaowei Zhu Zihao Dong Yang Liu NoLa 217 68 0 12 Oct 2021
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Zhaowei Zhu Tianyi Luo Yang Liu 243 40 0 12 Oct 2021