Linear convergence of SDCA in statistical estimation

26 January 2017

Papers citing "Linear convergence of SDCA in statistical estimation"

26 / 26 papers shown

Title
SAGA and Restricted Strong Convexity Chao Qu Yan Li Huan Xu 37 5 0 19 Feb 2017
Linear Convergence of SVRG in Statistical Estimation Chao Qu Yan Li Huan Xu 49 11 0 07 Nov 2016
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark Schmidt 242 1,216 0 16 Aug 2016
Fast Stochastic Methods for Nonsmooth Nonconvex Optimization Sashank J. Reddi S. Sra Barnabás Póczós Alex Smola 81 54 0 23 May 2016
Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction Xingguo Li R. Arora Han Liu Jarvis Haupt T. Zhao 41 68 0 09 May 2016
Primal-Dual Rates and Certificates Celestine Mendler-Dünner Simone Forte Martin Takáč Martin Jaggi 73 60 0 16 Feb 2016
SDCA without Duality, Regularization, and Individual Convexity Shai Shalev-Shwartz 39 104 0 04 Feb 2016
Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling Zeyuan Allen-Zhu Zheng Qu Peter Richtárik Yang Yuan 72 172 0 30 Dec 2015
Stop Wasting My Gradients: Practical SVRG Reza Babanezhad Mohamed Osama Ahmed Alim Virani Mark Schmidt Jakub Konecný Scott Sallinen 60 134 0 05 Nov 2015
Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives Zeyuan Allen-Zhu Yang Yuan 69 196 0 05 Jun 2015
Stochastic Dual Coordinate Ascent with Adaptive Probabilities Dominik Csiba Zheng Qu Peter Richtárik ODL 103 97 0 27 Feb 2015
Coordinate Descent with Arbitrary Sampling I: Algorithms and Complexity Zheng Qu Peter Richtárik 61 131 0 27 Dec 2014
Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi Virginia Smith Martin Takáč Jonathan Terhorst S. Krishnan Thomas Hofmann Michael I. Jordan 76 353 0 04 Sep 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 128 1,823 0 01 Jul 2014
A distributed block coordinate descent method for training $l_1$ regularized linear classifiers D. Mahajan S. Keerthi S. Sundararajan 132 35 0 18 May 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 147 738 0 19 Mar 2014
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 144 318 0 18 Feb 2014
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 289 1,246 0 10 Sep 2013
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang ODL 91 463 0 10 Sep 2013
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima Po-Ling Loh Martin J. Wainwright 236 516 0 10 May 2013
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 153 1,032 0 10 Sep 2012
A Proximal-Gradient Homotopy Method for the Sparse Least-Squares Problem Lin Xiao Tong Zhang 70 146 0 14 Mar 2012
High-dimensional regression with noisy and missing data: Provable guarantees with nonconvexity Po-Ling Loh Martin J. Wainwright 106 561 0 16 Sep 2011
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers S. Negahban Pradeep Ravikumar Martin J. Wainwright Bin Yu 360 1,378 0 13 Oct 2010
Nearly unbiased variable selection under minimax concave penalty Cun-Hui Zhang 305 3,557 0 25 Feb 2010
On the conditions used to prove oracle results for the Lasso Sara van de Geer Peter Buhlmann 237 731 0 05 Oct 2009