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Block coordinate descent (BCD) methods are widely used for large-scale numerical optimization because of their cheap iteration costs, low memory requirements, amenability to parallelization, and ability to exploit problem structure.
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Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition
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Block coordinate relaxation methods for nonparametric wavelet denoising
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Proximal points are on the fast track
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Iterative Methods for Sparse Linear Systems
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Convex Optimization
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Identifying active constraints via partial smoothness and prox-regularity
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The entire regularization path for the support vector machine
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Walk-sums and belief propagation in Gaussian graphical models
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Cubic regularization of Newton method and its global performance
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Piecewise linear regularized solution paths
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Greedy block coordinate descent for large scale gaussian process regression
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Covariance selection for nonchordal graphs via chordal embedding
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The group lasso for logistic regression
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Gaussian Belief Propagation: Theory and Application
D. Bickson · 2009
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Iterative hard thresholding for compressed sensing
T. Blumensath and M. E. Davies · 2009
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SINCO-a greedy coordinate ascent method for sparse inverse covariance selection problem
K. Scheinberg and I. Rish · 2009
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Tree block coordinate descent for MAP in graphical models
D. Sontag and T. Jaakkola · 2009
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Coordinate descent converges faster with the Gauss-Southwell rule than random selection
J. Nutini, M. Schmidt, I. H. Laradji, M. Friedlander, and H. Koepke · 2015
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Randomized dual coordinate ascent with arbitrary sampling
Z. Qu, P. Richtárik, and T. Zhang · 2015
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A. Srinivasan and E. Todorov · 2015
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Chordal graphs and semidefinite optimization
L. Vandenberghe and M. S. Andersen · 2015
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Nonlinear Programming
D. P. Bertsekas · 2016
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A fast active set block coordinate descent algorithm for ℓ 1 \ell_{1} -regularized least squares
M. De Santis, S. Lucidi, and F. Rinaldi · 2016
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Graphical Model Structure Learning with ℓ 1 \ell_{1} -Regularization
M. Schmidt · 2010
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LIBSVM: A library for support vector machines
C.-C. Chang and C.-J. Lin · 2011
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Nearest neighbor based greedy coordinate descent
I. S. Dhillon, P. K. Ravikumar, and A. Tewari · 2011
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Identifying active manifolds in regularization problems
W. L. Hare · 2011
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A homotopy algorithm for the quantile regression lasso and related piecewise linear problems
M. R. Osborne and B. A. Turlach · 2011
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Maximum block improvement and polynomial optimization
B. Chen, S. He, Z. Li, and S. Zhang · 2012
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Exploiting optimization for local graph clustering
K. Fountoulakis, F. Roosta-Khorasani, J. Shun, X. Cheng, and M. W. Mahoney · 2016
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Linear convergence of gradient and proximal-gradient methods under the Polyak- Ł \L{} ojasiewicz condition
H. Karimi, J. Nutini, and M. Schmidt · 2016
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Approximate Gaussian elimination for Laplacians - fast, sparse, and simple
R. Kyng and S. Sachdeva · 2016
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Coordinate-wise power method
Q. Lei, K. Zhong, and I. S. Dhillon · 2016
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Coordinate descent with arbitrary sampling I: Algorithms and complexity
Z. Qu and P. Richtárik · 2016
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Coordinate descent with arbitrary sampling II: Expected separable overapproximation
Z. Qu and P. Richtárik · 2016
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SDNA: Stochastic dual coordinate ascent for empirical risk minimization
Z. Qu, P. Richtárik, M. Takáč, and O. Fercoq · 2016
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Parallel coordinate descent methods for big data optimization
P. Richtárik and M. Takáč · 2016
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On optimal probabilities in stochastic coordinate descent methods
P. Richtárik and M. Takáč · 2016
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Inexact coordinate descent: Complexity and preconditioning
R. Tappenden, P. Richtárik, and J. Gondzio · 2016
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Asynchronous parallel greedy coordinate descent
Y. You, X. Lian, J. Liu, H.-F. Yu, I. S. Dhillon, J. Demmel, and C.-J. Hsieh · 2016
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D. Csiba and P. Richtárik · 2017
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Activity identification and local linear convergence of forward–backward-type methods
J. Liang, J. Fadili, and G. Peyré · 2017
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Adaptive sampling probabilities for non-smooth optimization
H. Namkoong, A. Sinha, S. Yadlowsky, and J. C. Duchi · 2017
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Faster coordinate descent via adaptive importance sampling
D. Perekrestenko, V. Cevher, and M. Jaggi · 2017
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Newton sketch: A linear-time optimization algorithm with linear-quadratic convergence
M. Pilanci and M. J. Wainwright · 2017
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Accelerated stochastic greedy coordinate descent by soft thresholding projection onto simplex
C.-B. Song, S. Cui, Y. Jiang, and S.-T. Xia · 2017
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Approximate steepest coordinate descent
S. U. Stich, A. Raj, and M. Jaggi · 2017
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Importance sampling for minibatches
D. Csiba and P. Richtárik · 2018
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A flexible coordinate descent method
K. Fountoulakis and R. Tappenden · 2018
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A comparative study on large scale kernelized support vector machines
D. Horn, A. Demircioğlu, B. Bischl, T. Glasmachers, and C. Weihs · 2018
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On matching pursuit and coordinate descent
F. Locatello, A. Raj, S. P. Karimireddy, G. Rätsch, B. Schölkopf, S. U. Stich, and M. Jaggi · 2018
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Accelerating greedy coordinate descent methods
H. Lu, R. M. Freund, and V. Mirrokni · 2018
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Efficient greedy coordinate descent for composite problems
S. P. Karimireddy, A. Koloskova, S. U. Stich, and M. Jaggi · 2019
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Random permutations fix a worst case for cyclic coordinate descent
C.-P. Lee and S. J. Wright · 2019
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Accelerating block coordinate descent methods with identification strategies
R. Lopes, S. A. Santos, and P. J. S. Silva · 2019
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“Active-set complexity” of proximal gradient: How long does it take to find the sparsity pattern?
J. Nutini, M. Schmidt, and W. Hare · 2019
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Greed meets sparsity: Understanding and improving greedy coordinate descent for sparse optimization
H. Fang, Z. Fan, Y. Sun, and M. Friedlander · 2020
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Convergence analysis of block coordinate algorithms with determinantal sampling
M. Mutny, M. Derezinski, and A. Krause · 2020
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A randomized coordinate descent method with volume sampling
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Efficient greedy coordinate descent via variable partitioning
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On complexity and convergence of high-order coordinate descent algorithms for smooth nonconvex box-constrained minimization
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