https://github.com/ntnu-ai-lab/rprop

Resilient backpropagation algorithm (RProp) optimizer implemented for Keras/TF
https://github.com/ntnu-ai-lab/rprop

Last synced: about 1 month ago
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Resilient backpropagation algorithm (RProp) optimizer implemented for Keras/TF

• Host: GitHub
• URL: https://github.com/ntnu-ai-lab/rprop
• Owner: ntnu-ai-lab
• Created: 2018-10-01T08:37:45.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-10-15T07:39:50.000Z (over 6 years ago)
• Last Synced: 2025-03-25T09:16:37.412Z (about 2 months ago)
• Language: Python
• Size: 1000 Bytes
• Stars: 3
• Watchers: 1
• Forks: 2
• Open Issues: 1
• Metadata Files:
  • Readme: README.org

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README

        
* About

This is a simple implementation of the Rprop (Riedman et al 1994) algorithm for

Keras, which should be easy to reimplement to Tensorflow.

* Usage

Just add to your codebase and implement, pass it along as a optimizer to your

"model.compile(optimizer=prop-optimizer-object)"