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NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1

License: MIT License

MATLAB 99.59% Python 0.39% M 0.01%
clustering-algorithm constrained-optimization data-analysis divergence gradient-descent matlab-toolbox matrix-factorization nmf nonnegative-matrix-factorization nonnegativity-constraints online-learning optimization-algorithms orthogonal probabilistic-matrix-factorization robust-optimization sparse-representations stochastic-optimizers

nmflibrary's Issues

demo.py file might not be working properly

I edited the demo.py file to compute the low rank symmetric rank of my 400 by 400 matrix. I know the symmetric rank of my symmetric matrix is 400, but the algorithm keeps giving me optimal rank 500 matrices that are not my original matrix. Thus, I suspect something is wrong with the demo.py file. I have noticed that no where in the file are the options specified. I have thus updated the file, and I think I have fixed the problem. Could you please look at it to confirm?

For citation about the program of nmf_sparse

Dear Dr. Hiroyuki Kasai

I hope you are well. Recently I have been using your program nmf_sparse of NMFLibrary for doing some research, and it's very well for running, many thanks to your comtributions. But I failed to find anything about the citation to this program of nmf_sparse from the GitHub website. Could you tell me about the citation about it if you don't mind?
I look forward to your reply!
Many thanks!

Yours sincerely,
Xelawk

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