lancopku/meProp

meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)

35
/ 100
Emerging

This project helps machine learning practitioners train deep neural networks significantly faster while improving model accuracy. It takes your existing neural network setup for tasks like natural language processing or image classification, and by intelligently updating only the most important parts of the network during training, it produces a more accurate and quickly-trained model. This is for machine learning engineers or researchers who build and train deep learning models.

110 stars. No commits in the last 6 months.

Use this if you need to accelerate the training of deep learning models for tasks such as dependency parsing, POS tagging, or image classification, and you want to achieve better accuracy than standard training methods.

Not ideal if your primary goal is extreme memory optimization or if you are not working with deep neural networks.

deep-learning-training neural-networks machine-learning-acceleration natural-language-processing image-recognition
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 8 / 25
Community 18 / 25

How are scores calculated?

Stars

110

Forks

20

Language

C#

License

Last pushed

Mar 29, 2022

Commits (30d)

0

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