Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Reyes, Juan Carlos De los"'
In this paper, we carry out a rigorous analysis of four-dimensional variational data assimilation problems for linear and semilinear parabolic equations with control in the initial condition, coming from a Lebesgue space. Due to the nature of the dat
Externí odkaz:
http://arxiv.org/abs/2303.00847
This paper focuses on the analysis of an optimal control problem governed by a nonsmooth quasilinear partial differential equation that models a stationary incompressible shear-thickening fluid. We start by studying the directional differentiability
Externí odkaz:
http://arxiv.org/abs/2203.02911
Autor:
Reyes, Juan Carlos De los
We investigate a family of bilevel imaging learning problems where the lower-level instance corresponds to a convex variational model involving first- and second-order nonsmooth sparsity-based regularizers. By using geometric properties of the primal
Externí odkaz:
http://arxiv.org/abs/2110.02273
We address the problem of optimal scale-dependent parameter learning in total variation image denoising. Such problems are formulated as bilevel optimization instances with total variation denoising problems as lower-level constraints. For the bileve
Externí odkaz:
http://arxiv.org/abs/2107.08100
In this paper we propose a second--order method for solving \emph{linear composite sparse optimization problems} consisting of minimizing the sum of a differentiable (possibly nonconvex function) and a nondifferentiable convex term. The composite non
Externí odkaz:
http://arxiv.org/abs/2009.01878
Autor:
Sherry, Ferdia, Benning, Martin, Reyes, Juan Carlos De los, Graves, Martin J., Maierhofer, Georg, Williams, Guy, Schönlieb, Carola-Bibiane, Ehrhardt, Matthias J.
The discovery of the theory of compressed sensing brought the realisation that many inverse problems can be solved even when measurements are "incomplete". This is particularly interesting in magnetic resonance imaging (MRI), where long acquisition t
Externí odkaz:
http://arxiv.org/abs/1906.08754
In this paper we propose a bilevel optimization approach for the placement of space and time observations in variational data assimilation problems. Within the framework of supervised learning, we consider a bilevel problem where the lower-level task
Externí odkaz:
http://arxiv.org/abs/1811.11505
Autor:
Reyes, Juan-Carlos De Los
Variational inequalities are an important mathematical tool for modelling free boundary problems that arise in different application areas. Due to the intricate nonsmooth structure of the resulting models, their analysis and optimization is a difficu
Externí odkaz:
http://arxiv.org/abs/1711.08418
We propose a nonsmooth trust-region method for solving optimization problems with locally Lipschitz continuous functions, with application to problems constrained by variational inequalities of the second kind. Under suitable assumptions on the model
Externí odkaz:
http://arxiv.org/abs/1711.03208
We consider the problem of image denoising in the presence of noise whose statistical properties are a combination of two different distributions. We focus on noise distributions that are frequently considered in applications, in particular mixtures
Externí odkaz:
http://arxiv.org/abs/1611.00690