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scientific article; zbMATH DE number 6982318

Language	Label	Description	Also known as
English	No label defined	scientific article; zbMATH DE number 6982318

Statements

scholarly article

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Peter Richtárik

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publication date

21 November 2018

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full work available at URL

https://arxiv.org/abs/1602.02283

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http://jmlr.csail.mit.edu/papers/v19/16-241.html

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zbMATH Keywords

empirical risk minimization

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importance sampling

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minibatching

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variance-reduced methods

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convex optimization

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describes a project that uses

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MaRDI profile type

MaRDI publication profile

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Large-Scale Machine Learning with Stochastic Gradient Descent

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Accelerated, Parallel, and Proximal Coordinate Descent

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Hybrid Deterministic-Stochastic Methods for Data Fitting

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Semi-stochastic coordinate descent

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An Accelerated Randomized Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization

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Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties

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Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning

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A random coordinate descent algorithm for optimization problems with composite objective function and linear coupled constraints

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Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm

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Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems

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Coordinate descent with arbitrary sampling I: algorithms and complexity<sup>†</sup>

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Coordinate descent with arbitrary sampling II: expected separable overapproximation

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Distributed Coordinate Descent Method for Learning with Big Data

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On optimal probabilities in stochastic coordinate descent methods

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Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function

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Parallel coordinate descent methods for big data optimization

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A Stochastic Approximation Method

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Erratum to: ``Minimizing finite sums with the stochastic average gradient''

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Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization

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Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization

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Pegasos: primal estimated sub-gradient solver for SVM

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A Proximal Stochastic Gradient Method with Progressive Variance Reduction

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Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization

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Identifiers

Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:4558169

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