MIMOSA is a currently ongoing research project funded by Agence Nationale de la Recherche from 2017 to 2021 (young researchers / JCJC program, no. ANR-16-CE33-0005-01). MIMOSA lies at the frontier between signal processing and operations research. It aims to propose new optimization strategies, based on mixed integer programming methods, in order to solve exactly some difficult L0-norm-based sparse approximation problems encountered in various signal processing applications.

Publications related to the MIMOSA project

  • R. Ben Mhenni, S. Bourguignon, J. Ninin and F. Schmidt, Spectral unmixing with sparsity and structuring constraints , in IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Amsterdam, The Netherlands, Sep. 2018. [paper]
  • M. Boudineau, H. Carfantan and S. Bourguignon, An L0 solution to sparse approximation problems with continuous dictionaries , in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, Canada, Apr. 2018.
  • R. Ben Mhenni, S. Bourguignon, J. Ninin and F. Schmidt, Méthodes exactes de démélange spectral en norme l0 et contraintes de parcimonie structurée à l’aide de MIP , in 19e conférence ROADEF, Société Française de Recherche Opérationnelle et Aide à la Décision, Lorient, France, February 2018. [slides]
  • R. Ben Mhenni, S. Bourguignon, J. Ninin and F. Schmidt, Démélange parcimonieux exact dans une approche supervisée en imagerie hyperspectrale , in Actes du 26e colloque GRETSI, Juan-les-Pins, Sep. 2017. [paper] [slides]

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