NDLI: A Low-Rank Approximation-Based Transductive Support Tensor Machine for Semisupervised Classification

Content Provider	IEEE Xplore Digital Library
Author	Xiaolan Liu Tengjiao Guo Lifang He Xiaowei Yang
Copyright Year	1992
Abstract	In the fields of machine learning, pattern recognition, image processing, and computer vision, the data are usually represented by the tensors. For the semisupervised tensor classification, the existing transductive support tensor machine (TSTM) needs to resort to iterative technique, which is very time-consuming. In order to overcome this shortcoming, in this paper, we extend the concave-convex procedure-based transductive support vector machine (CCCP-TSVM) to the tensor patterns and propose a low-rank approximation-based TSTM, in which the tensor rank-one decomposition is used to compute the inner product of the tensors. Theoretically, concave-convex procedure-based TSTM (CCCP-TSTM) is an extension of the linear CCCP-TSVM to tensor patterns. When the input patterns are vectors, CCCP-TSTM degenerates into the linear CCCP-TSVM. A set of experiments is conducted on 23 semisupervised classification tasks, which are generated from seven second-order face data sets, three third-order gait data sets, and two third-order image data sets, to illustrate the performance of the CCCP-TSTM. The results show that compared with CCCP-TSVM and TSTM, CCCP-TSTM provides significant performance gain in terms of test accuracy and training speed.
Sponsorship	IEEE Signal Processing Society
Page Count	14
File Size	3476305
Starting Page	1825
Ending Page	1838
File Format	PDF
ISSN	10577149
Volume Number	24
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Tensile stress Optimization Support vector machines Vectors Educational institutions Classification algorithms Semisupervised learning transductive support vector machine (TSVM) Concave-convex procedure semi-supervised tensor classification tensor rank-one decomposition transductive support tensor machine (TSTM)
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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