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AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks

AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks

6 December 2017
Aditya Devarakonda
Maxim Naumov
M. Garland
    ODL
ArXivPDFHTML

Papers citing "AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks"

14 / 14 papers shown
Title
GeoDA: a geometric framework for black-box adversarial attacks
GeoDA: a geometric framework for black-box adversarial attacks
A. Rahmati
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
H. Dai
MLAU
AAML
103
119
0
13 Mar 2020
Don't Decay the Learning Rate, Increase the Batch Size
Don't Decay the Learning Rate, Increase the Batch Size
Samuel L. Smith
Pieter-Jan Kindermans
Chris Ying
Quoc V. Le
ODL
97
994
0
01 Nov 2017
Feedforward and Recurrent Neural Networks Backward Propagation and
  Hessian in Matrix Form
Feedforward and Recurrent Neural Networks Backward Propagation and Hessian in Matrix Form
Maxim Naumov
46
9
0
16 Sep 2017
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
Priya Goyal
Piotr Dollár
Ross B. Girshick
P. Noordhuis
Lukasz Wesolowski
Aapo Kyrola
Andrew Tulloch
Yangqing Jia
Kaiming He
3DH
120
3,675
0
08 Jun 2017
Coupling Adaptive Batch Sizes with Learning Rates
Coupling Adaptive Batch Sizes with Learning Rates
Lukas Balles
Javier Romero
Philipp Hennig
ODL
122
110
0
15 Dec 2016
Big Batch SGD: Automated Inference using Adaptive Batch Sizes
Big Batch SGD: Automated Inference using Adaptive Batch Sizes
Soham De
A. Yadav
David Jacobs
Tom Goldstein
ODL
128
62
0
18 Oct 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
408
2,935
0
15 Sep 2016
Optimization Methods for Large-Scale Machine Learning
Optimization Methods for Large-Scale Machine Learning
Léon Bottou
Frank E. Curtis
J. Nocedal
225
3,205
0
15 Jun 2016
Distributed Deep Learning Using Synchronous Stochastic Gradient Descent
Distributed Deep Learning Using Synchronous Stochastic Gradient Descent
Dipankar Das
Sasikanth Avancha
Dheevatsa Mudigere
K. Vaidyanathan
Srinivas Sridharan
Dhiraj D. Kalamkar
Bharat Kaul
Pradeep Dubey
GNN
53
170
0
22 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.1K
193,426
0
10 Dec 2015
Stop Wasting My Gradients: Practical SVRG
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
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
432
43,234
0
11 Feb 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.5K
100,213
0
04 Sep 2014
Hybrid Deterministic-Stochastic Methods for Data Fitting
Hybrid Deterministic-Stochastic Methods for Data Fitting
M. Friedlander
Mark Schmidt
188
387
0
13 Apr 2011
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