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Tensor Train polynomial classifier in MATLAB©/Octave©

This package contains MATLAB/Octave implementations for training the Tensor Train polynomial classifier with both the least squares and logistic regression methods.

  1. Functions

  • [x, res, err]=ttls(a, b, n, r, gamma)

Trains the Tensor Train polynomial classifier with least squares.

  • [x, res, err]=ttlr(a, b, n, r, gamma)

Trains the Tensor Train polynomial classifier with logistic regression.

  • test_mnist

Trains the Tensor Train polynomial classifier on the MNIST benchmark.

  • test_usps

Trains the Tensor Train polynomial classifier on the USPS benchmark.

  1. Reference

Parallelized Tensor Train Learning of Polynomial Classifiers

https://arxiv.org/abs/1612.06505

Authors: Zhongming Chen, Kim Batselier, Johan A.K. Suykens, Ngai Wong

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Tensor Train polynomial classifier

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