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Extrapolation for Large-batch Training in Deep Learning

Extrapolation for Large-batch Training in Deep Learning

10 June 2020
Tao R. Lin
Lingjing Kong
Sebastian U. Stich
Martin Jaggi
ArXivPDFHTML

Papers citing "Extrapolation for Large-batch Training in Deep Learning"

13 / 13 papers shown
Title
Momentum-SAM: Sharpness Aware Minimization without Computational Overhead
Momentum-SAM: Sharpness Aware Minimization without Computational Overhead
Marlon Becker
Frederick Altrock
Benjamin Risse
76
5
0
22 Jan 2024
Faster Federated Learning with Decaying Number of Local SGD Steps
Faster Federated Learning with Decaying Number of Local SGD Steps
Jed Mills
Jia Hu
Geyong Min
FedML
30
7
0
16 May 2023
A New Perspective for Understanding Generalization Gap of Deep Neural
  Networks Trained with Large Batch Sizes
A New Perspective for Understanding Generalization Gap of Deep Neural Networks Trained with Large Batch Sizes
O. Oyedotun
Konstantinos Papadopoulos
Djamila Aouada
AI4CE
29
11
0
21 Oct 2022
Scalable K-FAC Training for Deep Neural Networks with Distributed
  Preconditioning
Scalable K-FAC Training for Deep Neural Networks with Distributed Preconditioning
Lin Zhang
S. Shi
Wei Wang
Bo-wen Li
28
10
0
30 Jun 2022
Towards Understanding Sharpness-Aware Minimization
Towards Understanding Sharpness-Aware Minimization
Maksym Andriushchenko
Nicolas Flammarion
AAML
24
133
0
13 Jun 2022
Tackling benign nonconvexity with smoothing and stochastic gradients
Tackling benign nonconvexity with smoothing and stochastic gradients
Harsh Vardhan
Sebastian U. Stich
20
8
0
18 Feb 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning
  Optimization Landscape
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape
Devansh Bisla
Jing Wang
A. Choromańska
25
34
0
20 Jan 2022
Implicit Gradient Alignment in Distributed and Federated Learning
Implicit Gradient Alignment in Distributed and Federated Learning
Yatin Dandi
Luis Barba
Martin Jaggi
FedML
18
31
0
25 Jun 2021
On Large-Cohort Training for Federated Learning
On Large-Cohort Training for Federated Learning
Zachary B. Charles
Zachary Garrett
Zhouyuan Huo
Sergei Shmulyian
Virginia Smith
FedML
21
112
0
15 Jun 2021
Consensus Control for Decentralized Deep Learning
Consensus Control for Decentralized Deep Learning
Lingjing Kong
Tao R. Lin
Anastasia Koloskova
Martin Jaggi
Sebastian U. Stich
19
75
0
09 Feb 2021
Stochastic Normalized Gradient Descent with Momentum for Large-Batch
  Training
Stochastic Normalized Gradient Descent with Momentum for Large-Batch Training
Shen-Yi Zhao
Chang-Wei Shi
Yin-Peng Xie
Wu-Jun Li
ODL
13
8
0
28 Jul 2020
Stochastic Nonconvex Optimization with Large Minibatches
Stochastic Nonconvex Optimization with Large Minibatches
Weiran Wang
Nathan Srebro
34
26
0
25 Sep 2017
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
281
2,888
0
15 Sep 2016
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