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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"

14 / 14 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
79
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
The Disharmony between BN and ReLU Causes Gradient Explosion, but is
  Offset by the Correlation between Activations
The Disharmony between BN and ReLU Causes Gradient Explosion, but is Offset by the Correlation between Activations
Inyoung Paik
Jaesik Choi
18
0
0
23 Apr 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
32
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
36
10
0
30 Jun 2022
Towards Understanding Sharpness-Aware Minimization
Towards Understanding Sharpness-Aware Minimization
Maksym Andriushchenko
Nicolas Flammarion
AAML
32
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
26
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
26
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
113
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
18
8
0
28 Jul 2020
Stochastic Nonconvex Optimization with Large Minibatches
Stochastic Nonconvex Optimization with Large Minibatches
Weiran Wang
Nathan Srebro
36
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
299
2,890
0
15 Sep 2016
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