A new accelerated algorithm for ill-conditioned ridge regression problems

DOI10.1007/s40314-017-0430-4zbMath1432.65077OpenAlexW2594699431MaRDI QIDQ725822

Tatiane C. Silva, Gislaine A. Periçaro, Ademir Alves Ribeiro

Publication date: 2 August 2018

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

Full work available at URL: https://doi.org/10.1007/s40314-017-0430-4

zbMATH Keywords

fixed pointridge regressionprimal-dual methodsaccelerated methods

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Numerical mathematical programming methods (65K05) Quadratic programming (90C20) Numerical methods based on nonlinear programming (49M37)

Related Items (2)

The complexity of primal-dual fixed point methods for ridge regression ⋮ Obtaining a threshold for the Stewart index and its extension to ridge regression

Uses Software

• ElemStatLearn

Cites Work

• A faster algorithm for ridge regression of reduced rank data
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• On Conjugate Convex Functions
• The elements of statistical learning. Data mining, inference, and prediction
• Benchmarking optimization software with performance profiles.
• On the dual formulation of regularized linear systems with convex risks
• Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization
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