BerivanIsik/sparse-random-networks
Implementation of the FedPM framework by the authors of the ICLR 2023 paper "Sparse Random Networks for Communication-Efficient Federated Learning".
This helps machine learning researchers implement a specific technique called FedPM to train models more efficiently. It takes your existing PyTorch models and datasets, and applies a method for reducing the amount of communication needed during federated learning. This is designed for academic researchers or practitioners working on distributed machine learning problems.
No commits in the last 6 months.
Use this if you are a researcher or engineer looking to experiment with or apply communication-efficient federated learning strategies.
Not ideal if you are looking for a general-purpose machine learning library or a solution for training models on a single machine.
Stars
30
Forks
2
Language
Python
License
MIT
Category
Last pushed
Feb 10, 2023
Commits (30d)
0
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