Newton-type methods with the proximal gradient step for sparse estimation

DOI10.1007/s43069-024-00307-xarXiv2211.16804OpenAlexW4393026494MaRDI QIDQ6130698

Joe Suzuki, Ryosuke Shimmura

Publication date: 3 April 2024

Published in: SN Operations Research Forum (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2211.16804

zbMATH Keywords

nonsmooth optimizationvariable selectionquasi-Newton methodlinear Newton approximation

Mathematics Subject Classification ID

Mathematical programming (90Cxx)

Cites Work

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• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• A regularized semi-smooth Newton method with projection steps for composite convex programs
• An efficient Hessian based algorithm for solving large-scale sparse group Lasso problems
• Forward-backward quasi-Newton methods for nonsmooth optimization problems
• A nonsmooth version of Newton's method
• Newton and Quasi-Newton Methods for a Class of Nonsmooth Equations and Related Problems
• A SemiSmooth Newton Method for Semidefinite Programs and its Applications in Electronic Structure Calculations
• Finite-Dimensional Variational Inequalities and Complementarity Problems
• Iterative Solution of Nonlinear Equations in Several Variables
• A Stochastic Semismooth Newton Method for Nonsmooth Nonconvex Optimization
• Model Selection and Estimation in Regression with Grouped Variables
• Convex analysis and monotone operator theory in Hilbert spaces