Matrix-wise $$\ell _0$$-constrained sparse nonnegative least squares
Author:
Funder
European Research Council
Fonds De La Recherche Scientifique - FNRS
Fonds Wetenschappelijk Onderzoek
Agence Nationale de la Recherche
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s10994-022-06260-2.pdf
Reference41 articles.
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2. Ben Mhenni, R., Bourguignon, S., & Ninin, J. (2021). Global optimization for sparse solution of least squares problems. Optimization Methods and Software, 1–30.
3. Bioucas-Dias, J. M., Plaza, A., Dobigeon, N., Parente, M., Du, Q., Gader, P., & Chanussot, J. (2012). Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(2), 354–379.
4. Blumensath, T., & Davies, M. E. (2009). Iterative hard thresholding for compressed sensing. Applied and computational harmonic analysis, 27(3), 265–274.
5. Bruckstein, A. M., Elad, M., & Zibulevsky, M. (2008). On the uniqueness of nonnegative sparse solutions to underdetermined systems of equations. IEEE Transactions on Information Theory, 54(11), 4813–4820.
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