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This monograph presents a class of algorithms called coordinate descent algorithms for mathematicians, statisticians, and engineers outside the field of optimization.
Relaxation Methods In Engineering Science - A Treatise On Approximate Computation
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A quadratic programming procedure
C. Hildreth · 1957
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A convex programming procedure
D. d’Esopo · 1959
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Minimizing certain convex functions
J. Warga · 1963
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Note – A note on the cyclic coordinate ascent method
N. Zadeh · 1970
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On search directions for minimization algorithms
M. J. Powell · 1973
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Maximum likelihood from incomplete data via the em algorithm
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Parallel and distributed computation: numerical methods , volume 23
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Dual ascent methods for problems with strictly convex costs and linear constraints: A unified approach
P. Tseng · 1990
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Asymptotic properties of the fenchel dual functional and applications to decomposition problems
A. Auslender · 1992
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On the convergence of the coordinate descent method for convex differentiable minimization
Z.-Q. Luo and P. Tseng · 1992
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Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values
P. Paatero and U. Tapper · 1994
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Basis pursuit
Shaobing Chen and D. Donoho · 1994
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Regression Shrinkage and Selection via the Lasso
R. Tibshirani · 1996
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Least Squares Support Vector Machine Classifiers
J. a. K. Suykens and J. Vandewalle · 1999
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On the convergence of the block nonlinear gauss–seidel method under convex constraints
L. Grippo and M. Sciandrone · 2000
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Convergence of a block coordinate descent method for nondifferentiable minimization
P. Tseng · 2001
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A simple and efficient algorithm for gene selection using sparse logistic regression
S. K. Shevade and S. S. Keerthi · 2003
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Solving large scale linear prediction problems using stochastic gradient descent algorithms
T. Zhang · 2004
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Regularization and variable selection via the elastic net
H. Zou and T. Hastie · 2005
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Model selection and estimation in regression with grouped variables
M. Yuan and Y. Lin · 2006
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Proximal thresholding algorithm for minimization over orthonormal bases
P. Combettes and J. Pesquet · 2007
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CVX: Matlab software for disciplined convex programming, 2008
M. Grant, S. Boyd, and Y. Ye · 2008
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Fixed-point continuation for ℓ 1 \ell_{1} -minimization: Methodology and convergence
E. T. Hale, W. Yin, and Y. Zhang · 2008
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Coordinate descent algorithms for lasso penalized regression
T. T. Wu and K. Lange · 2008
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A fast iterative shrinkage-thresholding algorithm for linear inverse problems
A. Beck and M. Teboulle · 2009
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Nonnegative matrix and tensor factorizations: applications to exploratory multi-way data analysis and blind source separation
A. Cichocki, R. Zdunek, A. H. Phan, and S.-i. Amari · 2009
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Coordinate descent optimization for ℓ 1 \ell_{1} minimization with application to compressed sensing; a greedy algorithm
Y. Li and S. Osher · 2009
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Robust stochastic approximation approach to stochastic programming
A. Nemirovski, A. Juditsky, G. Lan, and A. Shapiro · 2009
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A comparison of optimization methods and software for large-scale l1-regularized linear classification
C.-J. H. Guo-Xun Yuan, Kai-Wei Chang and C.-J. Lin · 2010
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Randomized methods for linear constraints: convergence rates and conditioning
D. Leventhal and A. S. Lewis · 2010
Cited alongside, same era.
Inexact block coordinate descent methods with application to non-negative matrix factorization
S. Bonettini · 2011
Cited alongside, same era.
Parallel coordinate descent for l1-regularized loss minimization
J. K. Bradley, A. Kyrola, D. Bickson, and C. Guestrin · 2011
Cited alongside, same era.
Libsvm: a library for support vector machines
C.-C. Chang and C.-J. Lin · 2011
Cited alongside, same era.
Nearest neighbor based greedy coordinate descent
I. S. Dhillon, P. K. Ravikumar, and A. Tewari · 2011
Cited alongside, same era.
Stochastic methods for ℓ 1 \ell_{1} -regularized loss minimization
S. Shalev-Shwartz and A. Tewari · 2011
Cited alongside, same era.
A class of randomized primal-dual algorithms for distributed optimization
J.-C. Pesquet and A. Repetti · 2014
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Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
P. Richtárik and M. Takáč · 2014
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Sparse bilinear logistic regression
J. V. Shi, Y. Xu, and R. G. Baraniuk · 2014
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A globally convergent algorithm for nonconvex optimization based on block coordinate update
Y. Xu and W. Yin · 2014
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Stochastic dual coordinate ascent with adaptive probabilities
D. Csiba, Z. Qu, and P. Richtarik · 2015
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A coordinate gradient descent method for ℓ 1-regularized convex minimization
S. Yun and K.-C. Toh · 2011
Cited alongside, same era.
A block coordinate gradient descent method for regularized convex separable optimization and covariance selection
S. Yun, P. Tseng, and K.-C. Toh · 2011
Cited alongside, same era.
Maximum block improvement and polynomial optimization
B. Chen, S. He, Z. Li, and S. Zhang · 2012
Cited alongside, same era.
Convergence rate analysis of map coordinate minimization algorithms
O. Meshi, A. Globerson, and T. S. Jaakkola · 2012
Cited alongside, same era.
Efficiency of coordinate descent methods on huge-scale optimization problems
Y. Nesterov · 2012
Cited alongside, same era.
Stochastic coordinate descent methods for regularized smooth and nonsmooth losses
Q. Tao, K. Kong, D. Chu, and G. Wu · 2012
Cited alongside, same era.
Stochastic block mirror descent methods for nonsmooth and stochastic optimization
C. D. Dang and G. Lan · 2015
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Accelerated, parallel, and proximal coordinate descent
O. Fercoq and P. Richtárik · 2015
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PASSCoDe: Parallel asynchronous stochastic dual coordinate descent
C.-J. Hsieh, H.-F. Yu, and I. S. Dhillon · 2015
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On convergence of the maximum block improvement method
Z. Li, A. Uschmajew, and S. Zhang · 2015
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Asynchronous stochastic coordinate descent: Parallelism and convergence properties
J. Liu and S. J. Wright · 2015
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An asynchronous parallel stochastic coordinate descent algorithm
J. Liu, S. J. Wright, C. Ré, V. Bittorf, and S. Sridhar · 2015
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Distributed block coordinate descent for minimizing partially separable functions
J. Mareček, P. Richtárik, and M. Takáč · 2015
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Coordinate descent converges faster with the gauss-southwell rule than random selection
J. Nutini, M. Schmidt, I. Laradji, M. Friedlander, and H. Koepke · 2015
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Efficient random coordinate descent algorithms for large-scale structured nonconvex optimization
A. Patrascu and I. Necoara · 2015
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On optimal probabilities in stochastic coordinate descent methods
P. Richtárik and M. Takáč · 2015
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Convex analysis
R. T. Rockafellar · 2015
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On the complexity of parallel coordinate descent
R. Tappenden, M. Takáč, and P. Richtárik · 2015
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Coordinate descent algorithms
S. J. Wright · 2015
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Alternating proximal gradient method for sparse nonnegative tucker decomposition
Y. Xu · 2015
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Block stochastic gradient iteration for convex and nonconvex optimization
Y. Xu and W. Yin · 2015
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Stochastic primal-dual coordinate method for regularized empirical risk minimization
Y. Zhang and X. Lin · 2015
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Global and local structure preserving sparse subspace learning: an iterative approach to unsupervised feature selection
N. Zhou, Y. Xu, H. Cheng, J. Fang, and W. Pedrycz · 2015
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Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling
Z. Allen-Zhu, P. Richtárik, Z. Qu, and Y. Yuan · 2016
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TMAC: A Toolbox of Modern Async-Parallel, Coordinate, Splitting, and Stochastic Methods
B. Edmunds, Z. Peng, and W. Yin · 2016
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Randomized primal-dual proximal block coordinate updates
X. Gao, Y. Xu, and S. Zhang · 2016
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On unbounded delay in asynchronous parallel fixed-point algorithms
R. Hannah and W. Yin · 2016
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A unified algorithmic framework for block-structured optimization involving big data: With applications in machine learning and signal processing
M. Hong, M. Razaviyayn, Z.-Q. Luo, and J.-S. Pang · 2016
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Parallel coordinate descent methods for big data optimization
P. Richtárik and M. Takáč · 2016
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Minimizing finite sums with the stochastic average gradient
M. Schmidt, N. L. Roux, and F. Bach · 2016
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Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization
S. Shalev-Shwartz and T. Zhang · 2016
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