Stable and Efficient Representation Learning with Nonnegativity Constraints

Abstract

Orthogonal matching pursuit (OMP) is an efficient approximation algorithm for computing sparse representations. However, prior research has shown that the representations computed by OMP may be of inferior quality, as they deliver suboptimal classification accuracy on several image datasets. We have found that this problem is caused by OMP’s relatively weak… (More)
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@inproceedings{Lin2014StableAE, title={Stable and Efficient Representation Learning with Nonnegativity Constraints}, author={Tsung-Han Lin and H. T. Kung}, booktitle={ICML}, year={2014} }