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Combining sparsity and dynamics: an efficient way

Angélique Drémeau 1 Patrick Héas 2 Cédric Herzet 3
2 ASPI - Applications of interacting particle systems to statistics
IRMAR - Institut de Recherche Mathématique de Rennes, Inria Rennes – Bretagne Atlantique
3 FLUMINANCE - Fluid Flow Analysis, Description and Control from Image Sequences
IRSTEA - Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture, Inria Rennes – Bretagne Atlantique
Abstract : Most linear sparse representation algorithms can be straightforwardly extended to non-linear models. Their performance however, relies on an efficient computation of the gradient of the objective function. In this paper, we focus on a particular non-linear model, defined as the nested composition of functions and propose to resort to a well-known technique from the theory of optimal control to compute the gradient. As a proof of con-cept, this computation is then implemented into the optimization procedure proposed byCan es et al., and applied to a geophysical dynamical model.
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Submitted on : Wednesday, December 17, 2014 - 10:10:57 AM
Last modification on : Friday, March 19, 2021 - 11:36:02 AM
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Angélique Drémeau, Patrick Héas, Cédric Herzet. Combining sparsity and dynamics: an efficient way. international - Traveling Workshop on Interactions between Sparse models and Technology (iTwist), Aug 2014, Namur, Belgium. ⟨hal-01096259⟩

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