Toward Fairness via Maximum Mean Discrepancy Regularization on Logits Space
Toward Fairness via Maximum Mean Discrepancy Regularization on Logits Space
About this item
Full title
Author / Creator
Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
Language
English
Formats
Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
Subjects
More information
Scope and Contents
Contents
Fairness has become increasingly pivotal in machine learning for high-risk applications such as machine learning in healthcare and facial recognition. However, we see the deficiency in the previous logits space constraint methods. Therefore, we propose a novel framework, Logits-MMD, that achieves the fairness condition by imposing constraints on ou...
Alternative Titles
Full title
Toward Fairness via Maximum Mean Discrepancy Regularization on Logits Space
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2929294736
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2929294736
Other Identifiers
E-ISSN
2331-8422
