Bilevel Methods for Image Reconstruction (Q5870782)

scientific article; zbMATH DE number 7644939

Language	Label	Description	Also known as
English	Bilevel Methods for Image Reconstruction	scientific article; zbMATH DE number 7644939

Statements

instance of

scholarly article

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title

Bilevel Methods for Image Reconstruction (English)

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Foundations and Trends® in Signal Processing

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publication date

23 January 2023

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full work available at URL

https://arxiv.org/abs/2109.09610

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zbMATH Keywords

decoding and inverse problems

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statistical/machine learning

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sparse representations

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describes a project that uses

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Learning regularization parameters of inverse problems via deep neural networks

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Total Generalized Variation

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A Limited Memory Algorithm for Bound Constrained Optimization

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Bilevel approaches for learning of variational imaging models

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Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

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Compressed sensing with coherent and redundant dictionaries

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Image recovery via total variation minimization and related problems

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An introduction to continuous optimization for imaging

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Insights Into Analysis Operator Learning: From Patch-Based Sparse Models to Higher Order MRFs

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Learnable Descent Algorithm for Nonsmooth Nonconvex Image Reconstruction

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Gradient-Based Solution Algorithms for a Class of Bilevel Optimization and Optimal Control Problems with a Nonsmooth Lower Level

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Annotated Bibliography on Bilevel Programming and Mathematical Programs with Equilibrium Constraints

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On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators

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Variational networks: an optimal control approach to early stopping variational methods for image restoration

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Analysis Operator Learning and its Application to Image Reconstruction

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Feasibility-based fixed point networks

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Bilevel optimization for calibrating point spread functions in blind deconvolution

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Robust regression using iteratively reweighted least-squares

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A bilevel approach for parameter learning in inverse problems

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Non-convex Optimization for Machine Learning

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Deep Convolutional Neural Network for Inverse Problems in Imaging

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Statistical inverse problems: discretization, model reduction and inverse crimes

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Adaptive restart of the optimized gradient method for convex optimization

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On the convergence analysis of the optimized gradient method

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The cosparse analysis model and algorithms

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Nonlinear total variation based noise removal algorithms

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How Stringent is the Linear Independence Assumption for Mathematical Programs with Complementarity Constraints?

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Infimal convolution regularizations with discrete \(\ell_1\)-type functionals

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Estimation of the mean of a multivariate normal distribution

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Identifiers

DOI

10.1561/2000000111

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:5870782