@inproceedings{23afffe0429746fe8f3e4eb7e1004d59,
title = "An overview of kernel based nonnegative matrix factorization",
abstract = "Nonnegative matrix factorization (NMF) is a recent method used to decompose a given data matrix into two nonnegative sparse factors. There are many techniques applied to enhance abilities of NMF, particularly kernel technique which discovering higher-order correlation between data points and obtaining more powerful latent features. This paper presents an overview of kernel methods on NMF along with its representation and recent variants. The development as well as algorithms for kernel based NMF are discussed and presented systematically.",
keywords = "Kernel based method, nonnegative matrix factorization (NMF)",
author = "Duong, {Viet Hang} and Hsieh, {Wen Chi} and Bao, {Pham The} and Wang, {Jia Ching}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Orange Technologies, ICOT 2014 ; Conference date: 20-09-2014 Through 23-09-2014",
year = "2014",
month = nov,
day = "12",
doi = "10.1109/ICOT.2014.6956641",
language = "???core.languages.en_GB???",
series = "IEEE International Conference on Orange Technologies, ICOT 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "227--231",
booktitle = "IEEE International Conference on Orange Technologies, ICOT 2014",
}