Transfer Learning using Computational Intelligence: A Survey

Publisher:
Elsevier
Publication Type:
Journal article
Citation:
Knowledge-Based Systems, 2015, 80 pp. 14 - 23
Issue Date:
2015-05-11
Full metadata record
Files in This Item:
Filename Description Size
ThumbnailKBS-Surney paper-references revised.pdfAccepted Manuscript Version579.23 kB
Adobe PDF
Abstract Transfer learning aims to provide a framework to utilize previously-acquired knowledge to solve new but similar problems much more quickly and effectively. In contrast to classical machine learning methods, transfer learning methods exploit the knowledge accumulated from data in auxiliary domains to facilitate predictive modeling consisting of different data patterns in the current domain. To improve the performance of existing transfer learning methods and handle the knowledge transfer process in real-world systems, ...
Please use this identifier to cite or link to this item: