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Evolving Loss Functions for Specific Image Augmentation Techniques

Evolving Loss Functions for Specific Image Augmentation Techniques

9 April 2024
Brandon Morgan
Dean Frederick Hougen
ArXivPDFHTML

Papers citing "Evolving Loss Functions for Specific Image Augmentation Techniques"

3 / 3 papers shown
Title
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning
Christian Raymond
Qi Chen
Bing Xue
Mengjie Zhang
FedML
29
11
0
19 Sep 2022
A disciplined approach to neural network hyper-parameters: Part 1 --
  learning rate, batch size, momentum, and weight decay
A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay
L. Smith
208
1,019
0
26 Mar 2018
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,634
0
03 Jul 2012
1