The nature of statistical learning theory
The nature of statistical learning theory
Color image processing and applications
Color image processing and applications
Optimal control by least squares support vector machines
Neural Networks
Rank-One Approximation to High Order Tensors
SIAM Journal on Matrix Analysis and Applications
SMO algorithm for least-squares SVM formulations
Neural Computation
The HumanID Gait Challenge Problem: Data Sets, Performance, and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminant Analysis with Tensor Representation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Rank-R Approximation of Tensors: Using Image-as-Matrix Representation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Sparse Image Coding Using a 3D Non-Negative Tensor Factorization
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Text classification: A least square support vector machine approach
Applied Soft Computing
Artificial Intelligence in Medicine
Knowledge and Information Systems
Active post-refined multimodality video semantic concept detection with tensor representation
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Model selection for the LS-SVM. Application to handwriting recognition
Pattern Recognition
Tensor Decompositions and Applications
SIAM Review
IEEE Transactions on Neural Networks
A novel technique for subpixel image classification based on support vector machine
IEEE Transactions on Image Processing
A survey of multilinear subspace learning for tensor data
Pattern Recognition
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Multitraining Support Vector Machine for Image Retrieval
IEEE Transactions on Image Processing
Multilinear Discriminant Analysis for Face Recognition
IEEE Transactions on Image Processing
MPCA: Multilinear Principal Component Analysis of Tensor Objects
IEEE Transactions on Neural Networks
Face Image Modeling by Multilinear Subspace Analysis With Missing Values
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In the fields of machine learning, image processing, and pattern recognition, the existing least squares support tensor machine for tensor classification involves a non-convex optimization problem and needs to be solved by the iterative technique. Obviously, it is very time-consuming and may suffer from local minima. In order to overcome these two shortcomings, in this paper, we present a tensor factorization based least squares support tensor machine (TFLS-STM) for tensor classification. In TFLS-STM, we combine the merits of least squares support vector machine (LS-SVM) and tensor rank-one decomposition. Theoretically, TFLS-STM is an extension of the linear LS-SVM to tensor patterns. When the input patterns are vectors, TFLS-STM degenerates into the standard linear LS-SVM. A set of experiments is conducted on six second-order face recognition datasets to illustrate the performance of TFLS-STM. The experimental results show that compared with the alternating projection LS-STM (APLS-STM) and LS-SVM, the training speed of TFLS-STM is faster than those of APLS-STM and LS-SVM. In term of testing accuracy, TFLS-STM is comparable with LS-SVM and is superiors to APLS-STM.