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...

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Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2024) vom: 30. Mai
1. Verfasser:	Hou, Ruibing (VerfasserIn)
Weitere Verfasser:	Chang, Hong, Ma, Bingpeng, Shan, Shiguang, Chen, Xilin
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2024
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article