SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
NeuFair: Neural Network Fairness Repair with Dropout
16 references·0 citing·33 second hop
NeuFair: Neural Network Fairness Repair with Dropout (2024)NeuFair: Neural Network Fairness Repair w…Wage Discrimination, Job Segregation, and Title VII of the Civil Rights Act of 1964 (2025)Wage Discrimination, Job Segr…Training data debugging for the fairness of machine learning software (2022)Training data debugging for t…NeuronFair (2022)NeuronFairFairness-aware configuration of machine learning libraries (2022)Fairness-aware configuration …Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline (2021)Fair Preprocessing: Towards U…Fair preprocessing: towards understanding compositional fairness of data transformers in machine learning pipeline (2021)Fair preprocessing: towards u…Bias in machine learning software: why? how? what to do? (2021)Bias in machine learning soft…"Ignorance and Prejudice" in Software Fairness (2021)"Ignorance and Prejudice" in …White-box fairness testing through adversarial sampling (2020)White-box fairness testing th…Fairway: a way to build fair ML software (2020)Fairway: a way to build fair …Preventing undesirable behavior of intelligent machines (2019)Preventing undesirable behavi…Software fairness (2018)Software fairnessMitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Automated directed fairness testing (2018)Automated directed fairness t…Certifying and Removing Disparate Impact (2015)Certifying and Removing Dispa…Decision Theory for Discrimination-Aware Classification (2012)Decision Theory for Discrimin…Discrimination-aware data mining (2008)Three naive Bayes approaches for discrimination-free classification (2010)Data preprocessing techniques for classification without discrimination (2011)A multidisciplinary survey on discrimination analysis (2013)Fairness in Machine Learning (2020)A Call to Action on Assessing and Mitigating Bias in Artificial Intelligence Applications for Mental Health (2022)Uniform Guidelines on Employee Selection Procedures (2007)Fairness through awareness (2012)European Union Regulations on Algorithmic Decision Making and a “Right to Explanation” (2017)A Survey on Bias and Fairness in Machine Learning (2021)Equality of Opportunity in Supervised Learning (2016)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Addressing bias in big data and AI for health care: A call for open science (2021)Fairness-Aware Classifier with Prejudice Remover Regularizer (2012)A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers (2023)Big Data's Disparate Impact (2014)Semantics derived automatically from language corpora contain human-like biases (2017)Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and unfairness within data management and analytics systems (2021)A Theory of Fairness, Competition, and Cooperation (1999)Incorporating Fairness into Game Theory and Economics (2011)Introduction to Stochastic Programming (2011)Protecting consumers from collusive prices due to AI (2020)Meaningful human control: actionable properties for AI system development (2022)Why we need to focus on developing ethical, responsible, and trustworthy artificial intelligence approaches for environmental science (2022)Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Exploring gender biases in ML and AI academic research through systematic literature review (2022)k-NN as an implementation of situation testing for discrimination discovery and prevention (2011)AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023)Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey (2023)Fairea: a model behaviour mutation approach to benchmarking bias mitigation methods (2021)In-Processing Modeling Techniques for Machine Learning Fairness: A Survey (2022)
this work references cited by second hop

References

  • 2015Certifying and Removing Disparate Impact1,827 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2012Decision Theory for Discrimination-Aware Classification300 cited
  • 2021Bias in machine learning software: why? how? what to do?224 cited
  • 2018Automated directed fairness testing200 cited
  • 2019Preventing undesirable behavior of intelligent machines143 cited
  • 2020Fairway: a way to build fair ML software140 cited
  • 2018Software fairness138 cited
  • 2020White-box fairness testing through adversarial sampling138 cited
  • 2021Fair preprocessing: towards understanding compositional fairness of data transformers in machine learning pipeline107 cited
  • 2021"Ignorance and Prejudice" in Software Fairness80 cited
  • 2021Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline75 cited
  • 2022NeuronFair63 cited
  • 2022Training data debugging for the fairness of machine learning software60 cited
  • 2022Fairness-aware configuration of machine learning libraries54 cited
  • 2025

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

Wage Discrimination, Job Segregation, and Title VII of the Civil Rights Act of 1964
43 cited

Cited by

No citing works inside the corpus for this window.