👋 This package provides research code and work is ongoing. If you are interested in using it in your own research, I'd love to hear from you and collaborate! Feel free to write: hong@udel.edu
Please cite the following papers for this technique:
David Hong, Tamara G. Kolda, Jed A. Duersch. "Generalized Canonical Polyadic Tensor Decomposition", SIAM Review 62:133-163, 2020. https://doi.org/10.1137/18M1203626 https://arxiv.org/abs/1808.07452
Tamara G. Kolda, David Hong. "Stochastic Gradients for Large-Scale Tensor Decomposition", SIAM Journal on Mathematics of Data Science 2:1066-1095, 2020. https://doi.org/10.1137/19M1266265 https://arxiv.org/abs/1906.01687
In BibTeX form:
@Article{hkd2020gcp,
title = "Generalized Canonical Polyadic Tensor Decomposition",
author = "David Hong and Tamara G. Kolda and Jed A. Duersch",
journal = "{SIAM} Review",
year = "2020",
volume = "62",
number = "1",
pages = "133--163",
DOI = "10.1137/18M1203626",
}
@Article{kh2020sgf,
title = "Stochastic Gradients for Large-Scale Tensor Decomposition",
author = "Tamara G. Kolda and David Hong",
journal = "{SIAM} Journal on Mathematics of Data Science",
year = "2020",
volume = "2",
number = "4",
pages = "1066--1095",
DOI = "10.1137/19M1266265",
}