An extended linearized alternating direction method of multipliers for fused-Lasso penalized linear regression
From MaRDI portal
Publication:6160373
DOI10.3934/jimo.2023030zbMath1524.90250OpenAlexW4324117809MaRDI QIDQ6160373
No author found.
Publication date: 23 June 2023
Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/jimo.2023030
variable selectionfused-Lassoextended linearized alternating direction method of multipliersextension step
Cites Work
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- An alternating direction method with continuation for nonconvex low rank minimization
- On the \(O(1/t)\) convergence rate of Ye-Yuan's modified alternating direction method of multipliers
- A note on the convergence of ADMM for linearly constrained convex optimization problems
- Properties and refinements of the fused Lasso
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- A new inexact alternating directions method for monotone variational inequalities
- Linearized alternating direction method of multipliers for sparse group and fused Lasso models
- Optimal distributed task scheduling in volunteer clouds
- Polynomial convergence of primal-dual path-following algorithms for symmetric cone programming based on wide neighborhoods and a new class of directions
- New tunnel-filled function method for discrete global optimization
- Fused Lasso penalized least absolute deviation estimator for high dimensional linear regression
- A generalized alternating direction method of multipliers with semi-proximal terms for convex composite conic programming
- An efficient algorithm for sparse inverse covariance matrix estimation based on dual formulation
- Filled function method to optimize supply chain transportation costs
- Inexact operator splitting method for monotone inclusion problems
- A penalty decomposition method for nuclear norm minimization with \(l_1\) norm fidelity term
- Linearized alternating direction method with parallel splitting and adaptive penalty for separable convex programs in machine learning
- Partial convolution for total variation deblurring and denoising by new linearized alternating direction method of multipliers with extension step
- A proximal point algorithm revisit on the alternating direction method of multipliers
- Multiplier and gradient methods
- A new infeasible-interior-point algorithm based on wide neighborhoods for symmetric cone programming
- A 2-block semi-proximal ADMM for solving the H-weighted nearest correlation matrix problem
- Linear Convergence and Metric Selection for Douglas-Rachford Splitting and ADMM
- A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science
- Alternating Direction Algorithms for $\ell_1$-Problems in Compressive Sensing
- Inertial Proximal ADMM for Linearly Constrained Separable Convex Optimization
- Spatial smoothing and hot spot detection for CGH data using the fused lasso
- Numerical Optimization
- Regression Shrinkage and Selection via The Lasso: A Retrospective
- Sparsity and Smoothness Via the Fused Lasso
- De-noising by soft-thresholding
- The Linearized Alternating Direction Method of Multipliers for Dantzig Selector
- Linearized augmented Lagrangian and alternating direction methods for nuclear norm minimization
- Rate of Convergence Analysis of Decomposition Methods Based on the Proximal Method of Multipliers for Convex Minimization
- A descent method for structured monotone variational inequalities
This page was built for publication: An extended linearized alternating direction method of multipliers for fused-Lasso penalized linear regression
