On optimal probabilities in stochastic coordinate descent methods
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Publication:315487
DOI10.1007/s11590-015-0916-1zbMath1353.90148arXiv1310.3438OpenAlexW2164075197WikidataQ59474745 ScholiaQ59474745MaRDI QIDQ315487
Publication date: 21 September 2016
Published in: Optimization Letters (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1310.3438
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Cites Work
- Unnamed Item
- Parallel coordinate descent methods for big data optimization
- Inexact coordinate descent: complexity and preconditioning
- On the complexity analysis of randomized block-coordinate descent methods
- Smooth minimization of nonsmooth functions with parallel coordinate descent methods
- Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
- Distributed Coordinate Descent Method for Learning with Big Data
- Coordinate descent with arbitrary sampling II: expected separable overapproximation
- Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems
- Separable approximations and decomposition methods for the augmented Lagrangian
- Stochastic Block Mirror Descent Methods for Nonsmooth and Stochastic Optimization
- Randomized Iterative Methods for Linear Systems
- Efficient Serial and Parallel Coordinate Descent Methods for Huge-Scale Truss Topology Design
- Random Coordinate Descent Algorithms for Multi-Agent Convex Optimization Over Networks
- Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
- Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization
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