Semi-Supervised Regression via Hierarchical Confidence Screening and Neighbor-Guided Pseudo-Label Calibration

Semi-supervised regression enhances model performance by effectively utilizing unlabeled data during training. Most existing methods select only a small subset of high-confidence unlabeled samples based on single confidence metrics to participate in model training. However, these approaches suffer f...

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Détails bibliographiques

Auteurs principaux:	Yunfei Mao, Bowen Yao
Format:	Artigo
Langue:	Inglês
Publié:	IEEE 2026-01-01
Collection:	IEEE Access
Sujets:	Confidence hierarchical confidence screening neighbor-guided pseudo-label calibration safe labeling technique semi-supervised regression
Accès en ligne:	https://ieeexplore.ieee.org/document/11474475/
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