Difference-of-Convex Algorithms for a Class of Sparse Group $\ell_0$ Regularized Optimization Problems
From MaRDI portal
Publication:5093646
DOI10.1137/21M1443455zbMath1496.90097arXiv2109.05251MaRDI QIDQ5093646
No author found.
Publication date: 29 July 2022
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2109.05251
Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Optimality conditions and duality in mathematical programming (90C46)
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Nearly unbiased variable selection under minimax concave penalty
- Relationship between the optimal solutions of least squares regularized with \(\ell_{0}\)-norm and constrained by \(k\)-sparsity
- DC approximation approaches for sparse optimization
- Iterative hard thresholding methods for \(l_0\) regularized convex cone programming
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- On the convergence of the proximal algorithm for nonsmooth functions involving analytic features
- A bilinear formulation for vector sparsity optimization
- Sparsest solutions of underdetermined linear systems via \( \ell _q\)-minimization for \(0<q\leqslant 1\)
- A proximal difference-of-convex algorithm with extrapolation
- DC programming and DCA: thirty years of developments
- DC formulations and algorithms for sparse optimization problems
- Calculus of the exponent of Kurdyka-Łojasiewicz inequality and its applications to linear convergence of first-order methods
- Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods
- Group variable selection via \(\ell_{p,0}\) regularization and application to optimal scoring
- An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems
- Optimization problems involving group sparsity terms
- A refined convergence analysis of \(\mathrm{pDCA}_{e}\) with applications to simultaneous sparse recovery and outlier detection
- Enhanced proximal DC algorithms with extrapolation for a class of structured nonsmooth DC minimization
- Asymptotic properties of bridge estimators in sparse high-dimensional regression models
- Newton method for \(\ell_0\)-regularized optimization
- Computing B-Stationary Points of Nonsmooth DC Programs
- A Continuous Exact $\ell_0$ Penalty (CEL0) for Least Squares Regularized Problem
- Restricted isometry properties and nonconvex compressive sensing
- Probing the Pareto Frontier for Basis Pursuit Solutions
- Optimization and nonsmooth analysis
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Sparse Reconstruction by Separable Approximation
- On the Reconstruction of Block-Sparse Signals With an Optimal Number of Measurements
- Block-Sparse Signals: Uncertainty Relations and Efficient Recovery
- Structured Compressed Sensing: From Theory to Applications
- A Highly Efficient Semismooth Newton Augmented Lagrangian Method for Solving Lasso Problems
- Multi-Tissue Decomposition of Diffusion MRI Signals via L0 Sparse-Group Estimation
- Group Sparse Recovery via the $\ell ^0(\ell ^2)$ Penalty: Theory and Algorithm
- Sparse Approximate Solutions to Linear Systems
- Robust Recovery of Signals From a Structured Union of Subspaces
- The Boosted Difference of Convex Functions Algorithm for Nonsmooth Functions
- Efficient Sparse Semismooth Newton Methods for the Clustered Lasso Problem
- Nonmonotone Enhanced Proximal DC Algorithms for a Class of Structured Nonsmooth DC Programming
- Difference-of-Convex Learning: Directional Stationarity, Optimality, and Sparsity
- A Unified View of Exact Continuous Penalties for $\ell_2$-$\ell_0$ Minimization
- Non-Lipschitz $\ell_{p}$-Regularization and Box Constrained Model for Image Restoration
- Group Sparse Optimization for Images Recovery Using Capped Folded Concave Functions
- A selective review of group selection in high-dimensional models
