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For composite nonsmooth optimization problems, Forward-Backward algorithm achieves model identification (e.g.
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Active sets, nonsmoothness, and sensitivity
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Randomized methods for linear constraints: convergence rates and conditioning
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Libsvm: a library for support vector machines
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Identifying active manifolds in regularization problems
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Scikit-learn: Machine learning in Python
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Stochastic methods for l1-regularized loss minimization
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Model selection with low complexity priors
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Iteration complexity analysis of block coordinate descent methods
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On faster convergence of cyclic block coordinate descent-type methods for strongly convex minimization
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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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Simple bounds for recovering low-complexity models
E. J. Candès and B. Recht · 2012
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Efficiency of coordinate descent methods on huge-scale optimization problems
Y. Nesterov · 2012
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Accelerated block-coordinate relaxation for regularized optimization
S. J. Wright · 2012
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On the convergence of block coordinate type methods
A. Beck and L. Tetruashvili · 2013
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A unified convergence analysis of block successive minimization methods for nonsmooth optimization
M. Razaviyayn, M. Hong, and Z.-Q. Luo · 2013
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On the nonasymptotic convergence of cyclic coordinate descent methods
A. Saha and A. Tewari · 2013
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J. Nutini, I. Laradji, and M. Schmidt · 2017
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Linear convergence and support vector identification of sequential minimal optimization
J. She and M. Schmidt · 2017
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A globally convergent algorithm for nonconvex optimization based on block coordinate update
Y. Xu and W. Yin · 2017
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Sensitivity analysis for mirror-stratifiable convex functions
J. Fadili, J. Malick, and G. Peyré · 2018
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Celer: a fast solver for the lasso with dual extrapolation
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Local convergence properties of SAGA/Prox-SVRG and acceleration
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Model consistency of partly smooth regularizers
S. Vaiter, G. Peyré, and J. Fadili · 2018
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Dual extrapolation for sparse generalized linear models
M. Massias, S. Vaiter, A. Gramfort, and J. Salmon · 2019
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Linear convergence of first order methods for non-strongly convex optimization
I. Necoara, Y. Nesterov, and F. Glineur · 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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Trajectory of alternating direction method of multipliers and adaptive acceleration
C. Poon and J. Liang · 2019
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Are we there yet? manifold identification of gradient-related proximal methods
Y. Sun, H. Jeong, J. Nutini, and M. Schmidt · 2019
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Implicit differentiation of lasso-type models for hyperparameter optimization
Q. Bertrand, Q. Klopfenstein, M. Blondel, S. Vaiter, A. Gramfort, and J. Salmon · 2020
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