Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning

18 February 2014

Papers citing "Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning"

13 / 113 papers shown

Title
Doubly Stochastic Primal-Dual Coordinate Method for Bilinear Saddle-Point Problem Adams Wei Yu Qihang Lin Tianbao Yang 22 7 0 14 Aug 2015
Distributed Mini-Batch SDCA Martin Takáč Peter Richtárik Nathan Srebro 19 50 0 29 Jul 2015
Accelerated Stochastic Gradient Descent for Minimizing Finite Sums Atsushi Nitanda ODL 27 24 0 09 Jun 2015
Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives Zeyuan Allen-Zhu Yang Yuan 16 194 0 05 Jun 2015
Stochastic Dual Coordinate Ascent with Adaptive Probabilities Dominik Csiba Zheng Qu Peter Richtárik ODL 53 97 0 27 Feb 2015
SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization Zheng Qu Peter Richtárik Martin Takáč Olivier Fercoq ODL 40 97 0 08 Feb 2015
Coordinate Descent with Arbitrary Sampling I: Algorithms and Complexity Zheng Qu Peter Richtárik 16 130 0 27 Dec 2014
Randomized Dual Coordinate Ascent with Arbitrary Sampling Zheng Qu Peter Richtárik Tong Zhang 30 58 0 21 Nov 2014
Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems Aaron Defazio T. Caetano Justin Domke 49 169 0 10 Jul 2014
A Coordinate Descent Primal-Dual Algorithm and Application to Distributed Asynchronous Optimization Pascal Bianchi W. Hachem F. Iutzeler 54 57 0 03 Jul 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 42 1,810 0 01 Jul 2014
Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods Jascha Narain Sohl-Dickstein Ben Poole Surya Ganguli ODL 53 125 0 09 Nov 2013
Minimizing Finite Sums with the Stochastic Average Gradient Mark W. Schmidt Nicolas Le Roux Francis R. Bach 52 1,243 0 10 Sep 2013