Fetching the paper…
Reading the bibliography…
In this paper we study decomposition methods based on separable approximations for minimizing the augmented Lagrangian.
Multiplier and gradient methods
Magnus R. Hestenes · 1969
Earlier work this paper cites.
A method for nonlinear constraints in minimization problems
Michael J. D. Powell · 1972
Earlier work this paper cites.
The multiplier method of Hestenes and Powell applied to convex programming
R. Tyrell Rockafellar · 1973
Earlier work this paper cites.
The use of Hestenes’ method of multipliers to resolve dual gaps in engineering system optimization
George Stephanopoulos and Arthur W. Westerberg · 1975
Earlier work this paper cites.
Augmented Lagrangians and applications of the proximal point algorithm in convex programming
R. Tyrell Rockafellar · 1976
Earlier work this paper cites.
Decomposition in large system optimization using the method of multipliers
N. Watanabe, Y. Nishimura, and M. Matsubara · 1978
Earlier work this paper cites.
An augmented Lagrangian method for block diagonal linear programming problems
Andrzej Ruszczyński · 1989
Earlier work this paper cites.
Scenarios and policy aggregation in optimization under uncertainty
R. Tyrell Rockafellar and Roger J.-B. Wets · 1991
Earlier work this paper cites.
A diagonal quadratic approximation method for large scale linear programs
John M. Mulvey and Andrzej Ruszczyński · 1992
Earlier work this paper cites.
An extension of the DQA algorithm to convex stochastic programs
Arno J. Berger, John M. Mulvey, and Andrzej Ruszczyński · 1994
Earlier work this paper cites.
A new scenario decomposition method for large scale stochastic optimization
John M. Mulvey and Andrzej Ruszczyński · 1995
Earlier work this paper cites.
On convergence of an augmented Lagrangian decomposition method for sparse convex optimization
Andrzej Ruszczyński · 1995
Earlier work this paper cites.
Constrained Optimization and Lagrange Multiplier Methods
Dimitri Bertsekas · 1996
Earlier work this paper cites.
Convergence of a block coordinate descent method for nondifferentiable minimization
Paul Tseng · 2001
Cited alongside, same era.
A dual coordinate descent method for large-scale linear svm
Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S Sathiya Keerthi, and S Sundararajan · 2008
Cited alongside, same era.
Coordinate descent optimization for l 1 l_{1} minimization with application to compressed sensing; a greedy algorithm
Yingying Li and Stanley Osher · 2009
Cited alongside, same era.
Stochastic methods for l 1 l_{1} regularized loss minimization
Shai Shalev-Shwartz and Ambuj Tewari · 2009
Cited alongside, same era.
Efficient block-coordinate descent algorithms for the group lasso
Zhiwei (Tony) Qin, Katya Scheinberg, and Donald Goldfarb · 2010
Cited alongside, same era.
Parallel coordinate descent for L1-regularized loss minimization
Parallel coordinate descent methods for big data optimization
Peter Richtárik and Martin Takáč · 2012
Later among the works it cites.
Block coordinate descent algorithms for large-scale sparse multiclass classification
Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara · 2013
Closest in time.
Parallel coordinate descent for the Adaboost problem
Olivier Fercoq · 2013
Closest in time.
Smoothed parallel coordinate descent method
Olivier Fercoq and Peter Richtárik · 2013
Closest in time.
Effcient accelerated coordinate descent methods and faster algorithms for solving linear systems
Yin Tat Lee and Aaron Sidford · 2013
Closest in time.
On the complexity analysis of randomized block-coordinate descent methods
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Joseph K. Bradley, Aapo Kyrola, Danny Bickson, and Carlos Guestrin · 2011
Cited alongside, same era.
Efficiency of randomized coordinate descent methods on minimization problems with a composite objective function
Peter Richtárik and Martin Takáč · 2011
Cited alongside, same era.
Efficiency of randomized coordinate descent methods on optimization problems with linearly coupled constraints
Ion Necoara, Yurii Nesterov, and Francois Glineur · 2012
Cited alongside, same era.
Ion Necoara and Andrei Patrascu · 2012
Cited alongside, same era.
Efficiency of coordinate descent methods on huge-scale optimization problems
Yurii Nesterov · 2012
Cited alongside, same era.
Efficient serial and parallel coordinate descent methods for huge-scale truss topology design
Peter Richtárik and Martin Takáč · 2012
Cited alongside, same era.
Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
Peter Richtárik and Martin Takáč · 2012
Cited alongside, same era.
Zhaosong Lu and Lin Xiao · 2013
Closest in time.
Randomized block coordinate non-monotone gradient method for a class of nonlinear programming
Zhaosong Lu and Lin Xiao · 2013
Closest in time.
Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization
Andrei Patrascu and Ion Necoara · 2013
Closest in time.
Accelerated mini-batch stochastic dual coordinate ascent
Shai Shalev-Shwartz and Tong Zhang · 2013
Closest in time.
Stochastic dual coordinate ascent methods for regularized loss minimization
Shai Shalev-Shwartz and Tong Zhang · 2013
Closest in time.
Mini-batch primal and dual methods for SVMs
Martin Takáč, Avleen Bijral, Peter Richtárik, and Nathan Srebro · 2013
Closest in time.
Inexact coordinate descent: complexity and preconditioning
Rachael Tappenden, Peter Richtárik, and Jacek Gondzio · 2013
Closest in time.