Aggregate subgradient method for nonsmooth DC optimization
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Publication:1996741
DOI10.1007/s11590-020-01586-zzbMath1460.90140OpenAlexW3025582638WikidataQ109595508 ScholiaQ109595508MaRDI QIDQ1996741
Sona Taheri, Napsu Karmitsa, Kaisa Joki, Marko M. Mäkelä, Adil M. Bagirov
Publication date: 26 February 2021
Published in: Optimization Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11590-020-01586-z
Related Items (6)
A Bundle Trust Region Algorithm for Minimizing Locally Lipschitz Functions ⋮ Convergence of the proximal bundle algorithm for nonsmooth nonconvex optimization problems ⋮ Robust piecewise linear L1-regression via nonsmooth DC optimization ⋮ New proximal bundle algorithm based on the gradient sampling method for nonsmooth nonconvex optimization with exact and inexact information ⋮ Steering exact penalty DCA for nonsmooth DC optimisation problems with equality and inequality constraints ⋮ An augmented subgradient method for minimizing nonsmooth DC functions
Uses Software
Cites Work
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- Primal-dual subgradient methods for convex problems
- Global convergence of a proximal linearized algorithm for difference of convex functions
- Subgradient method for nonconvex nonsmooth optimization
- Codifferential method for minimizing nonsmooth DC functions
- Globally convergent limited memory bundle method for large-scale nonsmooth optimization
- Discrete gradient method: Derivative-free method for nonsmooth optimization
- Two ``well-known properties of subgradient optimization
- Global optimality conditions for nonconvex optimization
- A bundle-Newton method for nonsmooth unconstrained minimization
- Solving a class of linearly constrained indefinite quadratic problems by DC algorithms
- An implementation of Shor's \(r\)-algorithm
- Minimizing nonsmooth DC functions via successive DC piecewise-affine approximations
- The DC (Difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems
- An effective line search for the subgradient method
- Methods of descent for nondifferentiable optimization
- An approximate ADMM for solving linearly constrained nonsmooth optimization problems with two blocks of variables
- A proximal bundle method for nonsmooth DC optimization utilizing nonconvex cutting planes
- Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems
- Introduction to Nonsmooth Optimization
- A Redistributed Proximal Bundle Method for Nonconvex Optimization
- A quasisecant method for minimizing nonsmooth functions
- Robust Stochastic Approximation Approach to Stochastic Programming
- Quasi-Newton Bundle-Type Methods for Nondifferentiable Convex Optimization
- Double Bundle Method for finding Clarke Stationary Points in Nonsmooth DC Programming
- Minimizing Nonconvex Nonsmooth Functions via Cutting Planes and Proximity Control
- A DC piecewise affine model and a bundling technique in nonconvex nonsmooth minimization
- New limited memory bundle method for large-scale nonsmooth optimization
- Convex analysis and global optimization
- Benchmarking optimization software with performance profiles.
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