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Kevin Kasa

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Preprint Oct 2026

Using Set Learning to Improve Set-Valued Classifiers on Long-tailed Data

Set-valued classification (SVC) offers a practical approach to communicating uncertainty while maintaining accuracy by predicting variable-sized sets per input rather than fixed-sized sets (e.g. top-1 or top-5). However, set-valued classifiers (SVCs) exhibit significantly degraded performance on long-tailed and imbalan...

Kevin Kasa, Scott C. Lowe, Graham W. Taylor · 0 citations

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