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We propose a new stochastic coordinate descent method for minimizing the sum of convex functions each of which depends on a small number of coordinates only.
A method of solving a convex programming problem with convergence rate O(1/k2)
Yurii Nesterov · 1983
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Fast training of support vector machines using sequential minimal optimization
John C Platt · 1999
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Smooth minimization of nonsmooth functions
Yurii Nesterov · 2005
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On accelerated proximal gradient methods for convex-concave optimization
Paul Tseng · 2008
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Coordinate descent algorithms for lasso penalized regression
Tong Tong Wu and Kenneth Lange · 2008
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A fast iterative shrinkage-thresholding algorithm for linear inverse problems
Amir Beck and Marc Teboulle · 2009
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Randomized methods for linear constraints: Convergence rates and conditioning
Dennis Leventhal and Adrian S. Lewis · 2010
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Parallel coordinate descent for L1-regularized loss minimization
Joseph K. Bradley, Aapo Kyrola, Danny Bickson, and Carlos Guestrin · 2011
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Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
Peter Richtárik and Martin Takáč · 2011
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Stochastic methods for ℓ 1 \ell_{1} -regularized loss minimization
Shai Shalev-Shwartz and Ambuj Tewari · 2011
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Efficiency of randomized coordinate descent methods on optimization problems with linearly coupled constraints
Ion Necoara, Yurii Nesterov, and Francois Glineur · 2012
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Efficiency of coordinate descent methods on huge-scale optimization problems
Yurii Nesterov · 2012
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Parallel coordinate descent methods for big data optimization problems
Peter Richtárik and Martin Takáč · 2012
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Proximal stochastic dual coordinate ascent
Shai Shalev-Shwartz and Tong Zhang · 2012
Cited alongside, same era.
Smooth minimization of nonsmooth functions by parallel coordinate descent
Distributed coordinate descent methods for composite minimization
Ion Necoara and Dragos Clipici · 2013
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Efficient parallel coordinate descent algorithm for convex optimization problems with separable constraints: application to distributed mpc
Ion Necoara and Dragos Clipici · 2013
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Distributed coordinate descent method for learning with big data
Peter Richtárik and Martin Takáč · 2013
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On optimal probabilities in stochastic coordinate descent methods
Peter Richtárik and Martin Takáč · 2013
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Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization
Shai Shalev-Shwartz and Tong Zhang · 2013
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Olivier Fercoq and Peter Richtárik · 2013
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Efficient accelerated coordinate descent methods and faster algorithms for solving linear systems
Yin Tat Lee and Aaron Sidford · 2013
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An asynchronous parallel stochastic coordinate descent algorithm
Ji Liu, Stephen J. Wright, Christopher Ré, and Victor Bittorf · 2013
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Mini-batch primal and dual methods for SVMs
Martin Takáč, Avleen Bijral, Peter Richtárik, and Nathan Srebro · 2013
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Inexact block coordinate descent method: complexity and preconditioning
Rachael Tappenden, Peter Richtárik, and Jacek Gondzio · 2013
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On the complexity analysis of randomized block-coordinate descent methods
Lin Xiao and Zhaosong Lu · 2013
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