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Neumann Optimizer: A Practical Optimization Algorithm for Deep Neural
  Networks

Neumann Optimizer: A Practical Optimization Algorithm for Deep Neural Networks

8 December 2017
Shankar Krishnan
Ying Xiao
Rif A. Saurous
    ODL
ArXivPDFHTML

Papers citing "Neumann Optimizer: A Practical Optimization Algorithm for Deep Neural Networks"

6 / 6 papers shown
Title
ASDL: A Unified Interface for Gradient Preconditioning in PyTorch
ASDL: A Unified Interface for Gradient Preconditioning in PyTorch
Kazuki Osawa
Satoki Ishikawa
Rio Yokota
Shigang Li
Torsten Hoefler
ODL
43
14
0
08 May 2023
Adaptive scaling of the learning rate by second order automatic
  differentiation
Adaptive scaling of the learning rate by second order automatic differentiation
F. Gournay
Alban Gossard
ODL
31
1
0
26 Oct 2022
M-FAC: Efficient Matrix-Free Approximations of Second-Order Information
M-FAC: Efficient Matrix-Free Approximations of Second-Order Information
Elias Frantar
Eldar Kurtic
Dan Alistarh
13
57
0
07 Jul 2021
Augment your batch: better training with larger batches
Augment your batch: better training with larger batches
Elad Hoffer
Tal Ben-Nun
Itay Hubara
Niv Giladi
Torsten Hoefler
Daniel Soudry
ODL
30
72
0
27 Jan 2019
Demystifying Parallel and Distributed Deep Learning: An In-Depth
  Concurrency Analysis
Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis
Tal Ben-Nun
Torsten Hoefler
GNN
33
702
0
26 Feb 2018
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
308
2,890
0
15 Sep 2016
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