Kareem S. Aggour, Bülent Yener. Adapting to data sparsity for efficient parallel PARAFAC tensor decomposition in Hadoop. In James Joshi, George Karypis, Ling Liu, Xiaohua Hu, Ronay Ak, Yinglong Xia, Weijia Xu, Aki-Hiro Sato, Sudarsan Rachuri, Lyle H. Ungar, Philip S. Yu, Rama Govindaraju, Toyotaro Suzumura, editors, 2016 IEEE International Conference on Big Data, BigData 2016, Washington DC, USA, December 5-8, 2016. pages 294-301, IEEE, 2016. [doi]
@inproceedings{AggourY16,
title = {Adapting to data sparsity for efficient parallel PARAFAC tensor decomposition in Hadoop},
author = {Kareem S. Aggour and Bülent Yener},
year = {2016},
doi = {10.1109/BigData.2016.7840615},
url = {http://dx.doi.org/10.1109/BigData.2016.7840615},
researchr = {https://researchr.org/publication/AggourY16},
cites = {0},
citedby = {0},
pages = {294-301},
booktitle = {2016 IEEE International Conference on Big Data, BigData 2016, Washington DC, USA, December 5-8, 2016},
editor = {James Joshi and George Karypis and Ling Liu and Xiaohua Hu and Ronay Ak and Yinglong Xia and Weijia Xu and Aki-Hiro Sato and Sudarsan Rachuri and Lyle H. Ungar and Philip S. Yu and Rama Govindaraju and Toyotaro Suzumura},
publisher = {IEEE},
isbn = {978-1-4673-9005-7},
}