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Sparse nonnegative matrix approximation: new formulations and algorithms

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Tandon,  R
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons76142

Sra,  S
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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MPIK-TR-193_[0].pdf
(Publisher version), 734KB

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Citation

Tandon, R., & Sra, S.(2010). Sparse nonnegative matrix approximation: new formulations and algorithms (193). Tübingen, Germany: Max Planck Institute for Biological Cybernetics.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-BE7E-9
Abstract
We introduce several new formulations for sparse nonnegative matrix approximation. Subsequently,
we solve these formulations by developing generic algorithms. Further, to help selecting a particular sparse formulation,
we briefly discuss the interpretation of each formulation. Finally, preliminary experiments are presented
to illustrate the behavior of our formulations and algorithms.