DARPA NGS2 HELIOS Project
PyTen is a python package containing the state-of-the-art tensor decomposition and completion algorithms for “filling in the gaps”' of recovering high-order tensor-structured datasets characterized by noisy and missing information. It is developed by DATA Lab and Info Lab at Texas A&M University supported by the DARPA NGS2 HELIOS project.
@article{song2019tensor,
title={Tensor completion algorithms in big data analytics},
author={Song, Qingquan and Ge, Hancheng and Caverlee, James and Hu, Xia},
journal={ACM Transactions on Knowledge Discovery from Data (TKDD)},
volume={13},
number={1},
pages={6},
year={2019},
publisher={ACM}
}
author = "Qingquan Song, Hancheng Ge, Xing Zhao, Xiao Huang, Ziwei Zhu, James Caverlee, Xia (Ben) Hu"
copyright = "Copyright 2016, The Helios Project"