Triplet Adaptation Framework for Robust Semi-Supervised Learning
Semi-supervised learning (SSL) suffers from severe performance degradation when labeled and unlabeled data come from inconsistent and imbalanced distribution. Nonetheless, there is a lack of theoretical guidance regarding a remedy for this issue. To bridge the gap between theoretical insights and pr...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 12 vom: 01. Nov., Seite 8056-8073
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| 1. Verfasser: |
Hou, Ruibing
(VerfasserIn) |
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| Weitere Verfasser: |
Chang, Hong,
Ma, Bingpeng,
Shan, Shiguang,
Chen, Xilin |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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