Software for Sparse Tensor Decomposition on Emerging Computing Architectures

E. Phipps and T. G. Kolda, , 2018

Generalized Canonical Polyadic Tensor Decomposition

D. Hong, T. G. Kolda and J. A. Duersch, arXiv, 2018

A Practical Randomized CP Tensor Decomposition

C. Battaglino, G. Ballard and T. G. Kolda, SIAM Journal on Matrix Analysis and Applications, 2018

Unsupervised Discovery of Demixed, Low-dimensional Neural Dynamics across Multiple Timescales through Tensor Components Analysis

A. H. Williams, T. H. Kim, F. Wang, S. Vyas, S. I. Ryu, K. V. Shenoy, M. Schnitzer, T. G. Kolda and S. Ganguli, Neuron, 2018

Triangular Alignment (TAME): A Tensor-based Approach for Higher-order Network Alignment

S. Mohammadi, D. F. Gleich, T. G. Kolda and A. Grama, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017

New Tensor Toolbox Website

The Tensor Toolbox is now fully open source and also has a new website at www.tensortoolbox.org.

Parallel Tensor Compression for Large-Scale Scientific Data

W. Austin, G. Ballard and T. G. Kolda, In IPDPS’16: Proceedings of the 30th IEEE International Parallel and Distributed Processing Symposium, 2016

Newton-Based Optimization for Kullback-Leibler Nonnegative Tensor Factorizations

S. Hansen, T. Plantenga and T. G. Kolda, Optimization Methods and Software, 2015

Numerical Optimization for Symmetric Tensor Decomposition

T. G. Kolda, Mathematical Programming B, 2015

Symmetric Orthogonal Tensor Decomposition is Trivial

T. G. Kolda, arXiv, 2015