Provable Methods for Non-negative Matrix Factorization

Nonnegative matrix factorization (NMF) is an important data-analysis problem which concerns factoring a given d n matrix A with nonnegative entries into matrices B and C where B and C are d k and k n with nonnegative entries. It has numerous applications including Object recognition, Topic Modelling...

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Bibliographic Details
Main Author:	Pani, Jagdeep
Other Authors:	Bhattacharyya, Chiranjib
Language:	en_US
Published:	2017
Subjects:	Non-negative Matrix Factorization (NMF) Data Analysis Non-Negative Matrix Factorization Uniqueness NMF Algorithms Singular Value Decompositon (SVD) Algorithm UTSVD NMF Algorithm Machine Learning Computer Science
Online Access:	http://hdl.handle.net/2005/2739 http://etd.ncsi.iisc.ernet.in/abstracts/3566/G27836-Abs.pdf

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http://hdl.handle.net/2005/2739
http://etd.ncsi.iisc.ernet.in/abstracts/3566/G27836-Abs.pdf

Provable Methods for Non-negative Matrix Factorization

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