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Kujifunza kwa Kuhamisha kwa Nusu-Simamizi×Uenezaji wa Lebo×
NyanjaUjifunzaji wa MashineUjifunzaji wa Mashine
FamiliaMachine learningMachine learning
Mwaka wa asili2010s2002
MwanzilishiPan, S. J. & Yang, Q. (formalized); wider communityZhu, X. & Ghahramani, Z.
AinaHybrid learning paradigmGraph-based semi-supervised classification
Chanzo asiliaZhuang, F., Qi, Z., Duan, K., Xi, D., Zhu, Y., Zhu, H., Xiong, H., & He, Q. (2021). A comprehensive survey on transfer learning. Proceedings of the IEEE, 109(1), 43–76. DOI ↗Zhu, X., & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University. link ↗
Majina mbadalaSSTL, semi-supervised domain adaptation, transfer learning with unlabeled data, few-label transfer learningLP, label spreading, graph-based semi-supervised learning, harmonic label propagation
Zinazohusiana43
MuhtasariSemi-supervised Transfer Learning combines knowledge transferred from a richly labeled source domain with the structure of abundant unlabeled target-domain data, using only a small set of labeled target examples to achieve strong generalization where full annotation is scarce or expensive.Label Propagation is a graph-based semi-supervised learning algorithm introduced by Zhu and Ghahramani in 2002 that spreads class labels from a small set of labeled nodes to a large set of unlabeled nodes by iteratively diffusing label information along the edges of a similarity graph, exploiting the manifold structure of the data.
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ScholarGateLinganisha mbinu: Semi-supervised Transfer Learning · Label Propagation. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare