Fair oversampling technique using heterogeneous clusters-Reference-Cited by-同舟云学术

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Fair oversampling technique using heterogeneous clusters

Published:2023-09 Issue: Volume:640 Page:119059
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Sonoda Ryosuke

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference41 articles.

1. Supervised machine learning: a review of classification techniques;Kotsiantis,2007

2. A survey on bias and fairness in machine learning;Mehrabi;ACM Comput. Surv.,2021

3. Equality of opportunity in supervised learning;Hardt,2016

4. Man is to computer programmer as woman is to homemaker? Debiasing word embeddings;Bolukbasi,2016

5. AdaFair: cumulative fairness adaptive boosting;Iosifidis,2019

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Migrate demographic group for fair Graph Neural Networks;Neural Networks;2024-07

2. Balancing Fairness: Unveiling the Potential of SMOTE-Driven Oversampling in AI Model Enhancement;2024 9th International Conference on Machine Learning Technologies (ICMLT);2024-05-24

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