A weighted mirror descent algorithm for nonsmooth convex optimization problem
From MaRDI portal
Publication:328453
DOI10.1007/s10957-016-0963-5zbMath1348.90464DBLPjournals/jota/LuongPRR16OpenAlexW2444301330WikidataQ59474421 ScholiaQ59474421MaRDI QIDQ328453
Panos Parpas, Daniel Rueckert, Duy V. N. Luong, Berc Rustem
Publication date: 20 October 2016
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10957-016-0963-5
Programming involving graphs or networks (90C35) Convex programming (90C25) Large-scale problems in mathematical programming (90C06)
Related Items (3)
Analogues of Switching Subgradient Schemes for Relatively Lipschitz-Continuous Convex Programming Problems ⋮ A Multilevel Framework for Sparse Optimization with Application to Inverse Covariance Estimation and Logistic Regression ⋮ On Modification of an Adaptive Stochastic Mirror Descent Algorithm for Convex Optimization Problems with Functional Constraints
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Proximal minimization algorithm with \(D\)-functions
- Mirror descent and nonlinear projected subgradient methods for convex optimization.
- Ergodic, primal convergence in dual subgradient schemes for convex programming
- The Ordered Subsets Mirror Descent Optimization Method with Applications to Tomography
- Convergence Analysis of a Proximal-Like Minimization Algorithm Using Bregman Functions
- Markov Random Field Modeling in Image Analysis
- Proximal Minimization Methods with Generalized Bregman Functions
This page was built for publication: A weighted mirror descent algorithm for nonsmooth convex optimization problem
