Fast proximity-gradient algorithms for structured convex optimization problems

DOI10.1016/j.acha.2015.11.004zbMath1346.65031OpenAlexW2173256896MaRDI QIDQ739473

Na Zhang, Qia Li

Publication date: 18 August 2016

Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.acha.2015.11.004

zbMATH Keywords

convex optimizationconvergence accelerationnumerical experimentquasi-Newton methodimage restorationoverrelaxationfixed-point proximity-gradient algorithms

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Methods of quasi-Newton type (90C53) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18)

Related Items (10)

A fixed-point proximity algorithm for recovering low-rank components from incomplete observation data with application to motion capture data refinement ⋮ An Adaptive Directional Haar Framelet-Based Reconstruction Algorithm for Parallel Magnetic Resonance Imaging ⋮ Preconditioned three-operator splitting algorithm with applications to image restoration ⋮ Convergence rate analysis for fixed-point iterations of generalized averaged nonexpansive operators ⋮ Primal-dual fixed point algorithm based on adapted metric method for solving convex minimization problem with application ⋮ A fast inertial primal-dual algorithm to composite optimization models with application to image restoration problems ⋮ Regularization with multilevel non-stationary tight framelets for image restoration ⋮ On the nonexpansive operators based on arbitrary metric: a degenerate analysis ⋮ Two-step fixed-point proximity algorithms for multi-block separable convex problems ⋮ A content-adaptive unstructured grid based regularized CT reconstruction method with a SART-type preconditioned fixed-point proximity algorithm

Cites Work

• Unnamed Item
• Unnamed Item
• Nonlinear total variation based noise removal algorithms
• Smooth minimization of non-smooth functions
• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• A primal-dual splitting method for convex optimization involving Lipschitzian, proximable and linear composite terms
• Wavelet frame based blind image inpainting
• Tight frame: an efficient way for high-resolution image reconstruction
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Multi-step fixed-point proximity algorithms for solving a class of optimization problems arising from image processing
• A framelet-based image inpainting algorithm
• Convergence Rate Analysis of Primal-Dual Splitting Schemes
• Proximity algorithms for image models: denoising
• A Parallel Splitting Method for Coupled Monotone Inclusions
• An alternating extragradient method for total variation-based image restoration from Poisson data
• The Split Bregman Method for L1-Regularized Problems
• Split Bregman Methods and Frame Based Image Restoration
• Monotone Operators and the Proximal Point Algorithm
• Wavelet Algorithms for High-Resolution Image Reconstruction
• A primal–dual fixed point algorithm for convex separable minimization with applications to image restoration
• EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization
• Stable signal recovery from incomplete and inaccurate measurements
• Convex analysis and monotone operator theory in Hilbert spaces

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