So sánh phương pháp

	Học chuyển giao bán giám sát	Lan truyền nhãn
Lĩnh vực	Học máy	Học máy
Họ	Machine learning	Machine learning
Năm ra đời	2010s	2002
Người khởi xướng	Pan, S. J. & Yang, Q. (formalized); wider community	Zhu, X. & Ghahramani, Z.
Loại	Hybrid learning paradigm	Graph-based semi-supervised classification
Công trình gốc	Zhuang, 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.	Zhu, X., & Ghahramani, Z. (2002). Learning from labeled and unlabeled data with label propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University.
Tên gọi khác	SSTL, semi-supervised domain adaptation, transfer learning with unlabeled data, few-label transfer learning	LP, label spreading, graph-based semi-supervised learning, harmonic label propagation
Liên quan	4	3
Tóm tắt	Semi-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.