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1506.03662
Cited By
Variance Reduced Stochastic Gradient Descent with Neighbors
11 June 2015
Thomas Hofmann
Aurelien Lucchi
Simon Lacoste-Julien
Brian McWilliams
ODL
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Papers citing
"Variance Reduced Stochastic Gradient Descent with Neighbors"
30 / 30 papers shown
Title
SOREL: A Stochastic Algorithm for Spectral Risks Minimization
Yuze Ge
Rujun Jiang
38
0
0
19 Jul 2024
AdaSelection: Accelerating Deep Learning Training through Data Subsampling
Minghe Zhang
Chaosheng Dong
Jinmiao Fu
Tianchen Zhou
Jia Liang
...
Bo Liu
Michinari Momma
Bryan Wang
Yan Gao
Yi Sun
35
3
0
19 Jun 2023
Stochastic Optimization for Spectral Risk Measures
Ronak R. Mehta
Vincent Roulet
Krishna Pillutla
Lang Liu
Zaïd Harchaoui
32
6
0
10 Dec 2022
Statistical and Computational Guarantees for Influence Diagnostics
Jillian R. Fisher
Lang Liu
Krishna Pillutla
Y. Choi
Zaïd Harchaoui
TDI
26
0
0
08 Dec 2022
BALPA: A Balanced Primal-Dual Algorithm for Nonsmooth Optimization with Application to Distributed Optimization
Luyao Guo
Jinde Cao
Xinli Shi
Shaofu Yang
15
0
0
06 Dec 2022
Green, Quantized Federated Learning over Wireless Networks: An Energy-Efficient Design
Minsu Kim
Walid Saad
Mohammad Mozaffari
Merouane Debbah
FedML
MQ
23
27
0
19 Jul 2022
Stochastic Gradient Methods with Preconditioned Updates
Abdurakhmon Sadiev
Aleksandr Beznosikov
Abdulla Jasem Almansoori
Dmitry Kamzolov
R. Tappenden
Martin Takáč
ODL
34
9
0
01 Jun 2022
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods
Aleksandr Beznosikov
Eduard A. Gorbunov
Hugo Berard
Nicolas Loizou
19
49
0
15 Feb 2022
MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks
R. Waleffe
J. Mohoney
Theodoros Rekatsinas
Shivaram Venkataraman
GNN
29
25
0
04 Feb 2022
Decentralized Stochastic Variance Reduced Extragradient Method
Luo Luo
Haishan Ye
27
7
0
01 Feb 2022
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization
Kaiwen Zhou
Anthony Man-Cho So
James Cheng
19
1
0
30 Sep 2021
Stochastic Polyak Stepsize with a Moving Target
Robert Mansel Gower
Aaron Defazio
Michael G. Rabbat
32
17
0
22 Jun 2021
SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning
Jianhong Wang
Yuan Zhang
Yunjie Gu
Tae-Kyun Kim
OffRL
FAtt
22
19
0
31 May 2021
SVRG Meets AdaGrad: Painless Variance Reduction
Benjamin Dubois-Taine
Sharan Vaswani
Reza Babanezhad
Mark W. Schmidt
Simon Lacoste-Julien
18
18
0
18 Feb 2021
Local SGD: Unified Theory and New Efficient Methods
Eduard A. Gorbunov
Filip Hanzely
Peter Richtárik
FedML
37
109
0
03 Nov 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters
Filip Hanzely
34
0
0
26 Aug 2020
Stochastic Hamiltonian Gradient Methods for Smooth Games
Nicolas Loizou
Hugo Berard
Alexia Jolicoeur-Martineau
Pascal Vincent
Simon Lacoste-Julien
Ioannis Mitliagkas
39
50
0
08 Jul 2020
Sampling and Update Frequencies in Proximal Variance-Reduced Stochastic Gradient Methods
Martin Morin
Pontus Giselsson
27
4
0
13 Feb 2020
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization
Samuel Horváth
Lihua Lei
Peter Richtárik
Michael I. Jordan
57
30
0
13 Feb 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems
Filip Hanzely
D. Kovalev
Peter Richtárik
35
17
0
11 Feb 2020
Reducing the variance in online optimization by transporting past gradients
Sébastien M. R. Arnold
Pierre-Antoine Manzagol
Reza Babanezhad
Ioannis Mitliagkas
Nicolas Le Roux
24
28
0
08 Jun 2019
Reducing Noise in GAN Training with Variance Reduced Extragradient
Tatjana Chavdarova
Gauthier Gidel
F. Fleuret
Simon Lacoste-Julien
25
134
0
18 Apr 2019
Cocoercivity, Smoothness and Bias in Variance-Reduced Stochastic Gradient Methods
Martin Morin
Pontus Giselsson
20
2
0
21 Mar 2019
Improved asynchronous parallel optimization analysis for stochastic incremental methods
Rémi Leblond
Fabian Pedregosa
Simon Lacoste-Julien
16
70
0
11 Jan 2018
Sub-sampled Cubic Regularization for Non-convex Optimization
Jonas Köhler
Aurelien Lucchi
19
164
0
16 May 2017
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure
A. Bietti
Julien Mairal
44
36
0
04 Oct 2016
Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method
Lihua Lei
Michael I. Jordan
29
96
0
12 Sep 2016
ASAGA: Asynchronous Parallel SAGA
Rémi Leblond
Fabian Pedregosa
Simon Lacoste-Julien
AI4TS
29
101
0
15 Jun 2016
Variance-Reduced Proximal Stochastic Gradient Descent for Non-convex Composite optimization
Xiyu Yu
Dacheng Tao
21
5
0
02 Jun 2016
A Simple Practical Accelerated Method for Finite Sums
Aaron Defazio
28
121
0
08 Feb 2016
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