
Support Spinor Machine
We generalize a support vector machine to a support spinor machine by us...
09/11/2017 ∙ by Kabin Kanjamapornkul, et al. ∙ 0 ∙ shareread it

Parallelized Tensor Train Learning of Polynomial Classifiers
In pattern classification, polynomial classifiers are wellstudied metho...
12/20/2016 ∙ by Zhongming Chen, et al. ∙ 0 ∙ shareread it

Principal Component Analysis with Tensor Train Subspace
Tensor train is a hierarchical tensor network structure that helps allev...
03/13/2018 ∙ by Wenqi Wang, et al. ∙ 0 ∙ shareread it

Tensor Train decomposition on TensorFlow (T3F)
Tensor Train decomposition is used across many branches of machine learn...
01/05/2018 ∙ by Alexander Novikov, et al. ∙ 0 ∙ shareread it

Matrix Product Operator Restricted Boltzmann Machines
A restricted Boltzmann machine (RBM) learns a probability distribution o...
11/12/2018 ∙ by Cong Chen, et al. ∙ 22 ∙ shareread it

A Nonlinear Kernel Support Matrix Machine for Matrix Learning
Tensor is a natural and compact representation for real world data which...
07/20/2017 ∙ by Yunfei Ye, et al. ∙ 0 ∙ shareread it

A complexity analysis of statistical learning algorithms
We apply informationbased complexity analysis to support vector machine...
12/19/2012 ∙ by Mark A. Kon, et al. ∙ 0 ∙ shareread it
A Support Tensor Train Machine
There has been growing interest in extending traditional vectorbased machine learning techniques to their tensor forms. An example is the support tensor machine (STM) that utilizes a rankone tensor to capture the data structure, thereby alleviating the overfitting and curse of dimensionality problems in the conventional support vector machine (SVM). However, the expressive power of a rankone tensor is restrictive for many realworld data. To overcome this limitation, we introduce a support tensor train machine (STTM) by replacing the rankone tensor in an STM with a tensor train. Experiments validate and confirm the superiority of an STTM over the SVM and STM.
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