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Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

Mësimi i Transferuar Gjysmë-mbikëqyrur×Mësimi i Transferueshëm×
FushaMësimi i makinësMësimi i makinës
FamiljaMachine learningMachine learning
Viti i origjinës2010s2010 (formalized); 1990s (early roots)
KrijuesiPan, S. J. & Yang, Q. (formalized); wider communityPan, S. J. & Yang, Q. (survey); Bengio, Y. (deep learning framing)
LlojiHybrid learning paradigmLearning paradigm
Burimi themeluesZhuang, 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 ↗Pan, S. J., & Yang, Q. (2010). A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345–1359. DOI ↗
Emërtime të tjeraSSTL, semi-supervised domain adaptation, transfer learning with unlabeled data, few-label transfer learningTL, domain adaptation, fine-tuning, pre-trained model adaptation
Të lidhura43
PërmbledhjaSemi-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.Transfer learning is a machine learning paradigm in which knowledge gained from training a model on a source task or domain is reused to improve learning on a different but related target task or domain. It is especially powerful when labeled data for the target task is scarce, and it underlies most modern deep learning applications in computer vision, natural language processing, and beyond.
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ScholarGateKrahasoni metodat: Semi-supervised Transfer Learning · Transfer Learning. Marrë më 2026-06-15 nga https://scholargate.app/sq/compare