Two sufficient descent three-term conjugate gradient methods for unconstrained optimization problems with applications in compressive sensing
From MaRDI portal
Publication:2142552
DOI10.1007/s12190-021-01589-8zbMath1493.90190OpenAlexW3179611553MaRDI QIDQ2142552
Benxin Zhang, Yu Feng Liu, Zhi Bin Zhu
Publication date: 27 May 2022
Published in: Journal of Applied Mathematics and Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s12190-021-01589-8
global convergencethree-term conjugate gradient methodcompressive sensingsufficient descent propertyunconstrained optimization problem\(\ell_1-\alpha \ell_2\) minimization
Related Items (8)
A new family of hybrid three-term conjugate gradient methods with applications in image restoration ⋮ A family of hybrid conjugate gradient method with restart procedure for unconstrained optimizations and image restorations ⋮ Two families of hybrid conjugate gradient methods with restart procedures and their applications ⋮ A three-term conjugate gradient algorithm with restart procedure to solve image restoration problems ⋮ A hybrid BB-type method for solving large scale unconstrained optimization ⋮ Two classes of spectral conjugate gradient methods for unconstrained optimizations ⋮ Two modified conjugate gradient methods for unconstrained optimization with applications in image restoration problems ⋮ An efficient conjugate gradient-based algorithm for unconstrained optimization and its projection extension to large-scale constrained nonlinear equations with applications in signal recovery and image denoising problems
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Globally convergent three-term conjugate gradient methods that use secant conditions and generate descent search directions for unconstrained optimization
- Two modified three-term conjugate gradient methods with sufficient descent property
- Open problems in nonlinear conjugate gradient algorithms for unconstrained optimization
- A new generalized shrinkage conjugate gradient method for sparse recovery
- A new conjugate gradient hard thresholding pursuit algorithm for sparse signal recovery
- Efficient generalized conjugate gradient algorithms. I: Theory
- Unified smoothing functions for absolute value equation associated with second-order cone
- A conjugate gradient algorithm for large-scale nonlinear equations and image restoration problems
- The modified PRP conjugate gradient algorithm under a non-descent line search and its application in the Muskingum model and image restoration problems
- A modified Dai-Liao conjugate gradient method for solving unconstrained optimization and image restoration problems
- A global convergence of LS-CD hybrid conjugate gradient method
- The PRP conjugate gradient algorithm with a modified WWP line search and its application in the image restoration problems
- Global convergence of a modified Fletcher-Reeves conjugate gradient method with Armijo-type line search
- Another hybrid conjugate gradient algorithm for unconstrained optimization
- Optimization theory and methods. Nonlinear programming
- Large sparse signal recovery by conjugate gradient algorithm based on smoothing technique
- Smoothing strategy along with conjugate gradient algorithm for signal reconstruction
- A three-parameter family of nonlinear conjugate gradient methods
- NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
- A descent modified Polak–Ribière–Polyak conjugate gradient method and its global convergence
- A nonlinear conjugate gradient method based on the MBFGS secant condition
- Algorithm 851
- GLOBAL CONVERGENCE OF TWO KINDS OF THREE-TERM CONJUGATE GRADIENT METHODS WITHOUT LINE SEARCH
- Minimization of $\ell_{1-2}$ for Compressed Sensing
- A New Conjugate Gradient Method with Guaranteed Descent and an Efficient Line Search
- Function minimization by conjugate gradients
- A Compressive-Sensing-Based Phaseless Imaging Method for Point-Like Dielectric Objects
- Some descent three-term conjugate gradient methods and their global convergence
- CUTEr and SifDec
- The conjugate gradient method in extremal problems
- Methods of conjugate gradients for solving linear systems
- New conjugacy conditions and related nonlinear conjugate gradient methods
- A modified BFGS method and its global convergence in nonconvex minimization
- Mathematical theory of optimization
- Benchmarking optimization software with performance profiles.
This page was built for publication: Two sufficient descent three-term conjugate gradient methods for unconstrained optimization problems with applications in compressive sensing
