<commit_before>SmallK Start Page
================

Introduction
----------------
SmallK is a high performance software package for low rank matrix approximation via the nonnegative matrix factorization (NMF). NMF is 
a low-rank approximation where a matrix is approximated 
by a product of two nonnegative factors. 
The role of NMF in data analytics has been as significant as the singular value decomposition (SVD). However, due to 
nonnegativity constraints, NMF has far superior interpretability of its results for many practical problems such as image processing, chemometrics, bioinformatics, topic modeling for text analytics and many more.
Our approach to solving the NMF nonconvex optimization
problem has proven convergence properties and is one of the most efficient 
methods developed to date.


SmallK home page
----------------
http://smallk.github.io

Acknowledgements
----------------

This work was funded by the DARPA XDATA program under AFRL Contract
FA8750-13-C-0002. Our DARPA
program manager is
[Dr. <NAME>](http://www.darpa.mil/Our_Work/I2O/Personnel/Dr_Christopher_White.aspx) and our
XDATA principal investigator is [Prof. <NAME>](http://www.cc.gatech.edu/~hpark/) of the 
Georgia Institute of Technology.

SmallK Copyright and Software License
======================================
SmallK is under copyright by the Georgia Institute of Technology, 2014. 
All source code is released under the 
[Apache 2.0](http://www.apache.org/licenses/LICENSE-2.0) license.<commit_msg>a few minor edits<commit_after>SmallK Start Page
================

Introduction
----------------
SmallK is a high performance software package for low rank matrix approximation via the nonnegative matrix factorization (NMF). NMF is 
a low-rank approximation where a matrix is approximated 
by a product of two nonnegative factors. 
The role of NMF in data analytics has been as significant as the singular value decomposition (SVD). However, due to 
nonnegativity constraints, NMF has far superior interpretability of its results for many practical problems such as image processing, chemometrics, bioinformatics, topic modeling for text analytics and many more.
Our approach to solving the NMF nonconvex optimization
problem has proven convergence properties and is one of the most efficient 
methods developed to date.


SmallK home page
----------------
[SmallK](http://smallk.github.io): http://smallk.github.io

Acknowledgements
----------------

This work was funded by the DARPA XDATA program under AFRL Contract
FA8750-13-C-0002. Our DARPA
program manager is
[Dr. <NAME>](http://www.darpa.mil/Our_Work/I2O/Personnel/Dr_Christopher_White.aspx) and our
XDATA principal investigator is [Professor <NAME>](http://www.cc.gatech.edu/~hpark/) of the 
Georgia Institute of Technology.

SmallK Copyright and Software License
======================================
SmallK is under copyright by the Georgia Institute of Technology, 2014. 
All source code is released under the 
[Apache 2.0](http://www.apache.org/licenses/LICENSE-2.0) license.
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