A subspace-accelerated split Bregman method for sparse data recovery with joint \(\ell_1\)-type regularizers

DOI10.1553/etna_vol53s406zbMath1451.65074arXiv1912.06805OpenAlexW3026631652MaRDI QIDQ2208931

Marco Viola, Valentina De Simone, Daniela di Serafino

Publication date: 28 October 2020

Published in: ETNA. Electronic Transactions on Numerical Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.06805

zbMATH Keywords

split Bregman methodmulti-period portfolio optimizationsubspace accelerationjoint \(\ell_1\)-type regularizers

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Portfolio theory (91G10)

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Cites Work

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• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• Restoration of images based on subspace optimization accelerating augmented Lagrangian approach
• Sample size selection in optimization methods for machine learning
• \(l_1\)-regularization for multi-period portfolio selection
• On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
• Modification of TV-ROF denoising model based on split Bregman iterations
• Minimizing quadratic functions subject to bound constraints with the rate of convergence and finite termination
• Multiple change-point detection: a selective overview
• Bregman operator splitting with variable stepsize for total variation image reconstruction
• Fused Lasso approach in portfolio selection
• Adaptive \(l_1\)-regularization for short-selling control in portfolio selection
• A second-order method for convex₁-regularized optimization with active-set prediction
• Sparse and stable Markowitz portfolios
• The Split Bregman Method for L1-Regularized Problems
• A Solver for Nonconvex Bound-Constrained Quadratic Optimization
• An algorithm for quadratic ℓ₁-regularized optimization with a flexible active-set strategy
• Monotone Operators and the Proximal Point Algorithm
• On the Maximization of a Concave Quadratic Function with Box Constraints
• Box Constrained Quadratic Programming with Proportioning and Projections
• FaRSA for ℓ₁-regularized convex optimization: local convergence and numerical experience
• Decomposition of images by the anisotropic Rudin-Osher-Fatemi model
• Sparsity and Smoothness Via the Fused Lasso
• A Two-Phase Gradient Method for Quadratic Programming Problems with a Single Linear Constraint and Bounds on the Variables
• On the numerical solution of bound constrained optimization problems
• A Reduced-Space Algorithm for Minimizing $\ell_1$-Regularized Convex Functions
• Convex Analysis
• An Iterative Regularization Method for Total Variation-Based Image Restoration