Modular proximal optimization for multidimensional total-variation regularization
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Publication:4614088
zbMath1411.90314arXiv1411.0589MaRDI QIDQ4614088
Publication date: 30 January 2019
Full work available at URL: https://arxiv.org/abs/1411.0589
Related Items (10)
An accelerated coordinate gradient descent algorithm for non-separable composite optimization ⋮ A unified approach for a 1D generalized total variation problem ⋮ Total Variation on a Tree ⋮ Graphon estimation via nearest‐neighbour algorithm and two‐dimensional fused‐lasso denoising ⋮ A unified analysis of convex and non-convex \(\ell_p\)-ball projection problems ⋮ A dynamic programming approach for generalized nearly isotonic optimization ⋮ A fast homotopy algorithm for gridless sparse recovery ⋮ Unnamed Item ⋮ A remark on accelerated block coordinate descent for computing the proximity operators of a sum of convex functions ⋮ Sparse spatially clustered coefficient model via adaptive regularization
Uses Software
Cites Work
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- Nonlinear total variation based noise removal algorithms
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Fast projection onto the simplex and the \(l_1\) ball
- On the ergodic convergence rates of a first-order primal-dual algorithm
- Domain decomposition methods with graph cuts algorithms for total variation minimization
- Finding best approximation pairs relative to two closed convex sets in Hilbert spaces
- Anisotropic total variation regularized \(L^1\) approximation and denoising/deblurring of 2D bar codes
- Properties and refinements of the fused Lasso
- On total variation minimization and surface evolution using parametric maximum flows
- Algorithms and software for total variation image reconstruction via first-order methods
- Variable fixing algorithms for the continuous quadratic Knapsack problem
- Estimating time-varying networks
- Performance of feature-selection methods in the classification of high-dimension data
- Adaptive total variation image deblurring: a majorization-minimization approach
- Local extremes, runs, strings and multiresolution. (With discussion)
- The convex geometry of linear inverse problems
- A first-order primal-dual algorithm for convex problems with applications to imaging
- The equivalence of the taut string algorithm and BV-regularization
- Adaptive piecewise polynomial estimation via trend filtering
- Pathwise coordinate optimization
- Proximal Splitting Methods in Signal Processing
- Analytical Evaluations of Double Integral Expressions Related to Total Variation
- Enforcing Group Structure through the Group Fused Lasso
- Parametric Maximum Flow Algorithms for Fast Total Variation Minimization
- The Split Bregman Method for L1-Regularized Problems
- Total Variation on a Tree
- Computing a Trust Region Step
- Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
- Anisotropic Smoothing Using Double Orientations
- The Group Lasso for Logistic Regression
- $\ell_1$ Trend Filtering
- Spatial smoothing and hot spot detection for CGH data using the fused lasso
- Decomposition through formalization in a product space
- LAPACK Users' Guide
- Monotone Operators and the Proximal Point Algorithm
- An active set strategy based on the augmented Lagrangian formulation for image restoration
- Numerical Optimization
- Trust Region Methods
- Sparse Reconstruction by Separable Approximation
- Decomposition of images by the anisotropic Rudin-Osher-Fatemi model
- Sparsity and Smoothness Via the Fused Lasso
- Newton's Method for Large Bound-Constrained Optimization Problems
- Projected Newton Methods for Optimization Problems with Simple Constraints
- A Limited Memory Algorithm for Bound Constrained Optimization
- Iterative Methods for Total Variation Denoising
- A remark on accelerated block coordinate descent for computing the proximity operators of a sum of convex functions
- Multiple Change-Point Estimation With a Total Variation Penalty
- Fast Image Recovery Using Variable Splitting and Constrained Optimization
- Learning with Submodular Functions: A Convex Optimization Perspective
- Model Selection and Estimation in Regression with Grouped Variables
- Scale Space and PDE Methods in Computer Vision
- Convex analysis and monotone operator theory in Hilbert spaces
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