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Estimate Sequences for Variance-Reduced Stochastic Composite
  Optimization

Estimate Sequences for Variance-Reduced Stochastic Composite Optimization

7 May 2019
A. Kulunchakov
Julien Mairal
ArXiv (abs)PDFHTML

Papers citing "Estimate Sequences for Variance-Reduced Stochastic Composite Optimization"

10 / 10 papers shown
Title
Estimate Sequences for Stochastic Composite Optimization: Variance
  Reduction, Acceleration, and Robustness to Noise
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise
A. Kulunchakov
Julien Mairal
63
45
0
25 Jan 2019
Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are
  Better Without the Outer Loop
Don't Jump Through Hoops and Remove Those Loops: SVRG and Katyusha are Better Without the Outer Loop
D. Kovalev
Samuel Horváth
Peter Richtárik
101
156
0
24 Jan 2019
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path
  Integrated Differential Estimator
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator
Cong Fang
C. J. Li
Zhouchen Lin
Tong Zhang
95
580
0
04 Jul 2018
Dimension-Free Iteration Complexity of Finite Sum Optimization Problems
Dimension-Free Iteration Complexity of Finite Sum Optimization Problems
Yossi Arjevani
Ohad Shamir
46
24
0
30 Jun 2016
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks
Julien Mairal
SSL
66
130
0
20 May 2016
Variance Reduced Stochastic Gradient Descent with Neighbors
Variance Reduced Stochastic Gradient Descent with Neighbors
Thomas Hofmann
Aurelien Lucchi
Simon Lacoste-Julien
Brian McWilliams
ODL
72
153
0
11 Jun 2015
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly
  Convex Composite Objectives
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
Aaron Defazio
Francis R. Bach
Simon Lacoste-Julien
ODL
137
1,828
0
01 Jul 2014
A Proximal Stochastic Gradient Method with Progressive Variance
  Reduction
A Proximal Stochastic Gradient Method with Progressive Variance Reduction
Lin Xiao
Tong Zhang
ODL
160
739
0
19 Mar 2014
Incremental Majorization-Minimization Optimization with Application to
  Large-Scale Machine Learning
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning
Julien Mairal
151
319
0
18 Feb 2014
Minimizing Finite Sums with the Stochastic Average Gradient
Minimizing Finite Sums with the Stochastic Average Gradient
Mark Schmidt
Nicolas Le Roux
Francis R. Bach
327
1,250
0
10 Sep 2013
1