A Comprehensive Survey on Transfer Learning

Transfer learning aims at improving the performance of target learners on target domains by transferring the knowledge contained in different but related source domains. In this way, the dependence on a large number of target-domain data can be reduced for constructing target learners. Due to the wi...

Celý popis

Podrobná bibliografia

Vydané v:	Proceedings of the IEEE Ročník 109; číslo 1; s. 43 - 76
Hlavní autori:	Zhuang, Fuzhen, Qi, Zhiyuan, Duan, Keyu, Xi, Dongbo, Zhu, Yongchun, Zhu, Hengshu, Xiong, Hui, He, Qing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptation models Covariance matrices Data models Domain adaptation Domains interpretation Machine learning Semisupervised learning Transfer learning
ISSN:	0018-9219, 1558-2256
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!