Cover Image

Why do we regularise in every iteration for imaging inverse problems?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Papoutsellis, Evangelos, Kereta, Zeljko, Papafitsoros, Kostas
Format:	Preprint
Published:	2024
Subjects:	Numerical Analysis Computer Vision and Pattern Recognition Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Split, Skip and Play: Variance-Reduced ProxSkip for Tomography Reconstruction is Extremely Fast
by: Papoutsellis, Evangelos, et al.
Published: (2026)

A Guide to Stochastic Optimisation for Large-Scale Inverse Problems
by: Ehrhardt, Matthias J., et al.
Published: (2024)

Stochastic Optimisation Framework using the Core Imaging Library and Synergistic Image Reconstruction Framework for PET Reconstruction
by: Papoutsellis, Evangelos, et al.
Published: (2024)

Deep unrolling for learning optimal spatially varying regularisation parameters for Total Generalised Variation
by: Vu, Thanh Trung, et al.
Published: (2025)

Off-the-grid regularisation for Poisson inverse problems
by: Lazzaretti, Marta, et al.
Published: (2024)

Dynamic inverse problems: Online regularisation theory
by: Jauhiainen, Jyrki, et al.
Published: (2026)

Methods based on Radon transform for non-affine deformable image registration of noisy images
by: Hurtado, Daniel E., et al.
Published: (2024)

Power of $\ell_1$-Norm Regularized Kaczmarz Algorithms for High-Order Tensor Recovery
by: Henneberger, Katherine, et al.
Published: (2024)

Tensor-Based Synchronization and the Low-Rankness of the Block Trifocal Tensor
by: Miao, Daniel, et al.
Published: (2024)

Hyperspectral Band Selection based on Generalized 3DTV and Tensor CUR Decomposition
by: Henneberger, Katherine, et al.
Published: (2024)

A Nonlocal Graph-PDE and Higher-Order Geometric Integration for Image Labeling
by: Sitenko, Dmitrij, et al.
Published: (2022)

Adaptive Extrapolated Proximal Gradient Methods with Variance Reduction for Composite Nonconvex Finite-Sum Minimization
by: Yuan, Ganzhao
Published: (2025)

Quaternion Nonlinear Transform-Induced Nuclear Norm for Low-Rank Tensor Completion
by: Karmakar, Biswarup, et al.
Published: (2026)

QuadSync: Quadrifocal Tensor Synchronization via Tucker Decomposition
by: Miao, Daniel, et al.
Published: (2026)

Learning Spatially Adaptive $\ell_1$-Norms Weights for Convolutional Synthesis Regularization
by: Kofler, Andreas, et al.
Published: (2025)

Learning Binary Sampling Patterns for Single-Pixel Imaging using Bilevel Optimisation
by: Tudosie, Serban Cristian, et al.
Published: (2025)

Transferable Foundation Models for Geometric Tasks on Point Cloud Representations: Geometric Neural Operators
by: Quackenbush, Blaine, et al.
Published: (2025)

Extending Neural Operators: Robust Handling of Functions Beyond the Training Set
by: Quackenbush, Blaine, et al.
Published: (2026)

An iterative process for the feasibility-seeking problem with sets that are unions of convex sets
by: Censor, Yair, et al.
Published: (2025)

Learning spatially adaptive sparsity level maps for arbitrary convolutional dictionaries
by: Schulz, Joshua, et al.
Published: (2026)

Second-order methods for quartically-regularised cubic polynomials, with applications to high-order tensor methods
by: Cartis, Coralia, et al.
Published: (2023)

Policy iteration for the deterministic control problems -- a viscosity approach
by: Tang, Wenpin, et al.
Published: (2023)

Finite element-based space-time total variation-type regularization of the inverse problem in electrocardiographic imaging
by: Haas, Manuel, et al.
Published: (2024)

Convergence analysis of equilibrium methods for inverse problems
by: Obmann, Daniel, et al.
Published: (2023)

An adaptive heavy ball method for ill-posed inverse problems
by: Jin, Qinian, et al.
Published: (2024)

On the convergence of stochastic variance reduced gradient for linear inverse problems
by: Jin, Bangti, et al.
Published: (2025)

Notes on the discretization of TV-norm regularized inverse potential problems
by: Baratchart, L, et al.
Published: (2025)

SOR-like iteration and FPI are consistent when they are equipped with certain optimal iterative parameters
by: Liu, Jiayu, et al.
Published: (2024)

Stochastic variance reduced gradient method for linear ill-posed inverse problems
by: Jin, Qinian, et al.
Published: (2024)

Convergence analysis of multi-step one-shot methods for linear inverse problems
by: Bonazzoli, Marcella, et al.
Published: (2022)

Accelerating operator Sinkhorn iteration with overrelaxation
by: Soma, Tasuku, et al.
Published: (2024)

Separation-free exponential fitting with structured noise, with applications to inverse problems in parabolic PDEs
by: Katz, Rami, et al.
Published: (2025)

Numerically stable variants of overrelaxation for operator Sinkhorn iteration
by: Eisenmann, Henrik, et al.
Published: (2026)

Parallel-in-iteration optimization using multigrid reduction-in-time
by: Araújo, G. H. M., et al.
Published: (2026)

Data-driven approaches to inverse problems
by: Schönlieb, Carola-Bibiane, et al.
Published: (2025)

Preconditioned iterative solvers for constrained high-order implicit shock tracking methods
by: Vandergrift, Jakob, et al.
Published: (2024)

Policy iteration for nonconvex viscous Hamilton--Jacobi equations
by: Guo, Xiaoqin, et al.
Published: (2025)

A primal-dual algorithm for image reconstruction with input-convex neural network regularizers
by: Ehrhardt, Matthias J., et al.
Published: (2024)

A generalization of the Newton-based matrix splitting iteration method for generalized absolute value equations
by: Li, Xuehua, et al.
Published: (2023)

An inexact framework of the Newton-based matrix splitting iterative method for the generalized absolute value equation
by: Yu, Dongmei, et al.
Published: (2021)