Least Square Support Tensor Regression Machine Based on Submatrix of the Tensor
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-09
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
For tensor regression problem, a novel method, called least square support tensor regression machine based on submatrix of a tensor (LS-STRM-SMT), is proposed.
LS-STRM-SMT is a method which can be applied to deal with tensor regression problem more efficiently.
First, we develop least square support matrix regression machine (LS-SMRM) and propose a fixed point algorithm to solve it.
And then LS-STRM-SMT for tensor data is proposed.
Inspired by the relation between photochrome and the gray pictures, we reformulate the tensor sample training set and form the new model (LS-STRM-SMT) for tensor regression problem.
With the introduction of projection matrices and another fixed point algorithm, we turn the LS-STRM-SMT model into several related LS-SMRM models which are solved by the algorithm for LS-SMRM.
Since the fixed point algorithm is used twice while solving the LS-STRM-SMT problem, we call the algorithm dual fixed point algorithm (DFPA).
Our method (LS-STRM-SMT) has been compared with several typical support tensor regression machines (STRMs).
From theoretical point of view, our algorithm has less parameters and its computational complexity should be lower, especially when the rank of submatrix K is small.
The numerical experiments indicate that our algorithm has a better performance.
American Psychological Association (APA)
Shu, Tuo& Yang, Zhi-Xia. 2017. Least Square Support Tensor Regression Machine Based on Submatrix of the Tensor. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1190276
Modern Language Association (MLA)
Shu, Tuo& Yang, Zhi-Xia. Least Square Support Tensor Regression Machine Based on Submatrix of the Tensor. Mathematical Problems in Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1190276
American Medical Association (AMA)
Shu, Tuo& Yang, Zhi-Xia. Least Square Support Tensor Regression Machine Based on Submatrix of the Tensor. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1190276
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190276