Minimum Determinant Constraint for Non-negative Matrix Factorization

Authors:
Reinhard Schachtner;Gerhard Pöppel;Ana Maria Tomé;Elmar W. Lang
Affiliations:
CIMLG / Biophysics, University of Regensburg, Regensburg, Germany 93040 and Infineon Technologies AG, Regensburg, Germany 93049;Infineon Technologies AG, Regensburg, Germany 93049;DETI / IEETA, Universidade de Aveiro, Aveiro, Portugal 3810;CIMLG / Biophysics, University of Regensburg, Regensburg, Germany 93040
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

Citing 3
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Abstract

We propose a determinant criterion to constrain the solutions of non-negative matrix factorization problems and achieve unique and optimal solutions in a general setting, provided an exact solution exists. We demonstrate with illustrative examples how optimal solutions are obtained using our new algorithm detNMF and discuss the difference to NMF algorithms imposing sparsity constraints.