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Fairness in Visual Clustering: A Novel Transformer Clustering Approach

Fairness in Visual Clustering: A Novel Transformer Clustering Approach

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2802661328

Fairness in Visual Clustering: A Novel Transformer Clustering Approach

About this item

Full title

Fairness in Visual Clustering: A Novel Transformer Clustering Approach

Publisher

Ithaca: Cornell University Library, arXiv.org

Journal title

arXiv.org, 2023-09

Language

English

Formats

Publication information

Publisher

Ithaca: Cornell University Library, arXiv.org

Subjects

More information

Scope and Contents

Contents

Promoting fairness for deep clustering models in unsupervised clustering settings to reduce demographic bias is a challenging goal. This is because of the limitation of large-scale balanced data with well-annotated labels for sensitive or protected attributes. In this paper, we first evaluate demographic bias in deep clustering models from the pers...

Alternative Titles

Full title

Fairness in Visual Clustering: A Novel Transformer Clustering Approach

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2802661328

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2802661328

Other Identifiers

E-ISSN

2331-8422

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