Bias in Machine Learning Software: Why? How? What to do?

25 May 2021

Joymallya Chakraborty

Papers citing "Bias in Machine Learning Software: Why? How? What to do?"

21 / 21 papers shown

Title
Intersectional Divergence: Measuring Fairness in Regression Joe Germino Nuno Moniz Nitesh V. Chawla FaML 68 0 0 01 May 2025
Whence Is A Model Fair? Fixing Fairness Bugs via Propensity Score Matching Kewen Peng Yicheng Yang Hao Zhuo 32 0 0 23 Apr 2025
FairSense: Long-Term Fairness Analysis of ML-Enabled Systems Yining She Sumon Biswas Christian Kastner Eunsuk Kang 45 0 0 03 Jan 2025
Towards Robust Training Datasets for Machine Learning with Ontologies: A Case Study for Emergency Road Vehicle Detection Lynn Vonderhaar Timothy Elvira T. Procko Omar Ochoa 39 0 0 21 Jun 2024
Generative AI Voting: Fair Collective Choice is Resilient to LLM Biases and Inconsistencies Srijoni Majumdar Edith Elkind Evangelos Pournaras SyDa 55 1 0 31 May 2024
Predicting Fairness of ML Software Configurations Salvador Robles Herrera Verya Monjezi V. Kreinovich Ashutosh Trivedi Saeid Tizpaz-Niari 29 1 0 29 Apr 2024
SAFER: Situation Aware Facial Emotion Recognition M. Palash Bharat K. Bhargava 30 0 0 14 Jun 2023
Causality-Aided Trade-off Analysis for Machine Learning Fairness Zhenlan Ji Pingchuan Ma Shuai Wang Yanhui Li FaML 34 7 0 22 May 2023
Latent Imitator: Generating Natural Individual Discriminatory Instances for Black-Box Fairness Testing Yisong Xiao Aishan Liu Tianlin Li Xianglong Liu 22 26 0 19 May 2023
Fairness-Aware Data Valuation for Supervised Learning José P. Pombal Pedro Saleiro Mário A. T. Figueiredo P. Bizarro TDI 43 3 0 29 Mar 2023
Preventing Discriminatory Decision-making in Evolving Data Streams Zichong Wang N. Saxena Tongjia Yu Sneha Karki Tyler Zetty ... Shanlin Zhou Dukka B Kc I. Stockwell Albert Bifet Wenbin Zhang FaML 33 19 0 16 Feb 2023
Less, but Stronger: On the Value of Strong Heuristics in Semi-supervised Learning for Software Analytics Huy Tu Tim Menzies 28 0 0 03 Feb 2023
What are the Machine Learning best practices reported by practitioners on Stack Exchange? Anamaria Mojica-Hanke A. Bayona Mario Linares-Vásquez Steffen Herbold Fabio A. González HAI 24 6 0 25 Jan 2023
Don't Lie to Me: Avoiding Malicious Explanations with STEALTH Lauren Alvarez Tim Menzies 34 2 0 25 Jan 2023
Towards Understanding Fairness and its Composition in Ensemble Machine Learning Usman Gohar Sumon Biswas Hridesh Rajan FaML FedML 13 24 0 08 Dec 2022
Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning Damien Dablain Bartosz Krawczyk Nitesh V. Chawla FaML 26 19 0 13 Jul 2022
Fair-SSL: Building fair ML Software with less data Joymallya Chakraborty Suvodeep Majumder Huy Tu SyDa 11 5 0 03 Nov 2021
Fair Enough: Searching for Sufficient Measures of Fairness Suvodeep Majumder Joymallya Chakraborty Gina R. Bai Kathryn T. Stolee Tim Menzies 22 26 0 25 Oct 2021
Developing a novel fair-loan-predictor through a multi-sensitive debiasing pipeline: DualFair Ashutosh Kumar Singh Jashandeep Singh Ariba Khan Amar Gupta FaML 21 3 0 17 Oct 2021
Productivity, Portability, Performance: Data-Centric Python Yiheng Wang Yao Zhang Yanzhang Wang Yan Wan Jiao Wang Zhongyuan Wu Yuhao Yang Bowen She 54 95 0 01 Jul 2021
Astraea: Grammar-based Fairness Testing E. Soremekun Sakshi Udeshi Sudipta Chattopadhyay 26 27 0 06 Oct 2020