Path following in the exact penalty method of convex programming

DOI10.1007/s10589-015-9732-xzbMath1343.90063arXiv1201.3593OpenAlexW2115944913WikidataQ36047827 ScholiaQ36047827MaRDI QIDQ493687

Hua Zhou, Kenneth L. Lange

Publication date: 4 September 2015

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1201.3593

zbMATH Keywords

convex programmingpath followingexact penalty

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25)

Related Items

Iterative Method for Non-Stationary Mixed Variational Inequalities, On the structure of regularization paths for piecewise differentiable regularization terms, MM algorithms for geometric and signomial programming

Uses Software

• Matlab
• ConvexLAR

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonlinear total variation based noise removal algorithms
• The solution path of the generalized lasso
• Linear and nonlinear programming.
• Algorithms and applications for approximate nonnegative matrix factorization
• A tutorial on geometric programming
• The geometric programming dual to the extinction probability problem in simple branching processes
• An algorithm for total variation minimization and applications
• Least angle regression. (With discussion)
• MM algorithms for geometric and signomial programming
• Theory of Globally Convergent Probability-One Homotopies for Nonlinear Programming
• On the Bumpy Road to the Dominant Mode
• The Split Bregman Method for L1-Regularized Problems
• An Algorithm for Restricted Least Squares Regression
• Numerical Analysis for Statisticians
• Numerical Linear Algebra Aspects of Globally Convergent Homotopy Methods
• Geometric Programming: Methods, Computations and Applications
• Maximum likelihood estimates for multinomial probabilities via geometric programming
• Geometric Programming
• A new approach to variable selection in least squares problems
• Interior Methods for Nonlinear Optimization
• Semidefinite Programming
• A Generic Path Algorithm for Regularized Statistical Estimation
• Digital Circuit Optimization via Geometric Programming
• Learning the parts of objects by non-negative matrix factorization
• Non-Linear Programming Via Penalty Functions
• Best approximation in inner product spaces