NDLI: Transfer learning by centroid pivoted mapping in noisy environment

Content Provider	Springer Nature Link
Author	Huy, Thach Nguyen Tong, Bin Shao, Hao Suzuki, Eishin
Copyright Year	2012
Abstract	Transfer learning is a widely investigated learning paradigm that is initially proposed to reuse informative knowledge from related domains, as supervised information in the target domain is scarce while it is sufficiently available in the multiple source domains. One of the challenging issues in transfer learning is how to handle the distribution differences between the source domains and the target domain. Most studies in the research field implicitly assume that data distributions from the source domains and the target domain are similar in a well-designed feature space. However, it is often the case that label assignments for data in the source domains and the target domain are significantly different. Therefore, in reality even if the distribution difference between a source domain and a target domain is reduced, the knowledge from multiple source domains is not well transferred to the target domain unless the label information is carefully considered. In addition, noisy data often emerge in real world applications. Therefore, considering how to handle noisy data in the transfer learning setting is a challenging problem, as noisy data inevitably cause a side effect during the knowledge transfer. Due to the above reasons, in this paper, we are motivated to propose a robust framework against noise in the transfer learning setting. We also explicitly consider the difference in data distributions and label assignments among multiple source domains and the target domain. Experimental results on one synthetic data set, three UCI data sets and one real world text data set in different noise levels demonstrate the effectiveness of our method.
Starting Page	39
Ending Page	60
Page Count	22
File Format	PDF
ISSN	09259902
Journal	Journal of Intelligent Information Systems
Volume Number	41
Issue Number	1
e-ISSN	15737675
Language	English
Publisher	Springer US
Publisher Date	2012-11-09
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Supervised transfer learning Cross-task classification Noise handling Information Storage and Retrieval Data Structures, Cryptology and Information Theory Artificial Intelligence (incl. Robotics) Business Information Systems Document Preparation and Text Processing
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Information Systems Software Hardware and Architecture

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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