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06/01/2022
The effect of time discretization on the solution of parabolic PDEs with ANNs
We investigate the resolution of parabolic PDEs via Extreme Learning Mac...
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05/26/2022
Automatic parameter selection for the TGV regularizer in image restoration under Poisson noise
We address the image restoration problem under Poisson noise corruption....
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10/07/2021
Time Series Forecasting Using Manifold Learning
We address a three-tier numerical framework based on manifold learning f...
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08/03/2021
Numerical Solution of Stiff Ordinary Differential Equations with Random Projection Neural Networks
We propose a numerical scheme based on Random Projection Neural Networks...
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04/30/2021
Directional TGV-based image restoration under Poisson noise
We are interested in the restoration of noisy and blurry images where th...
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04/29/2021
TGV-based restoration of Poissonian images with automatic estimation of the regularization parameter
The problem of restoring images corrupted by Poisson noise is common in ...
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02/26/2021
Sparse Approximations with Interior Point Methods
Large-scale optimization problems that seek sparse solutions have become...
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02/10/2021
A View of Regularized Approaches for Image Segmentation
Image segmentation is a central topic in image processing and computer v...
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08/05/2020
Spatially Adaptive Regularization in Image Segmentation
We modify the total-variation-regularized image segmentation model propo...
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07/31/2020
LSOS: Line-search Second-Order Stochastic optimization methods
We develop a line-search second-order algorithmic framework for optimiza...
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04/02/2020
Using gradient directions to get global convergence of Newton-type methods
The renewed interest in Steepest Descent (SD) methods following the work...
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12/14/2019
A subspace-accelerated split Bregman method for sparse data recovery with joint l1-type regularizers
We propose a subspace-accelerated Bregman method for the linearly constr...
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10/07/2019