NDLI: Multiclass Semi-Supervised Boosting Using Similarity Learning

Content Provider	IEEE Xplore Digital Library
Author	Tanha, J. Saberian, M.J. Van Someren, M.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Univ. of California, San Diego, La Jolla, CA, USA (Saberian, M.J.) \|\| Inf. Inst., Univ. of Amsterdam, Amsterdam, Netherlands (Tanha, J.; Van Someren, M.)
Abstract	In this paper, we consider the multiclass semi-supervised classification problem. A boosting algorithm is proposed to solve the multiclass problem directly. The proposed multiclass approach uses a new multiclass loss function, which includes two terms. The first term is the cost of the multiclass margin and the second term is a regularization term on unlabeled data. The regularization term is used to minimize the inconsistency between the pair wise similarity and the classifier predictions. It assigns the soft labels weighted with the similarity between unlabeled and labeled examples. We then derive a boosting algorithm, named CD-MSSBoost, from the proposed loss function using coordinate gradient descent. The derived algorithm is further used for learning optimal similarity function for a given data. Our experiments on a number of UCI datasets show that CD-MSSBoost outperforms the state-of-the-art methods to multiclass semi-supervised learning.
Sponsorship	Toshiba
Starting Page	1205
Ending Page	1210
File Size	204250
Page Count	6
File Format	PDF
ISBN	9780769551081
ISSN	15504786
DOI	10.1109/ICDM.2013.108
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Boosting Semisupervised learning Prediction algorithms Training Optimization Algorithm design and analysis Similarity learning Semi-Supervised Learning Multiclass classification
Content Type	Text
Resource Type	Article

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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
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