https://github.com/anishacharya/optimization-mavericks

This repository provides a unified framework to perform Optimization experiments across Stochastic, Mini-Batch, Decentralized and Federated Setting.
https://github.com/anishacharya/optimization-mavericks

federated-learning optimization-algorithms robust-optimization robust-statistics sgd

Last synced: about 1 month ago
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This repository provides a unified framework to perform Optimization experiments across Stochastic, Mini-Batch, Decentralized and Federated Setting.

• Host: GitHub
• URL: https://github.com/anishacharya/optimization-mavericks
• Owner: anishacharya
• License: mit
• Created: 2021-01-09T00:36:13.000Z (about 5 years ago)
• Default Branch: main
• Last Pushed: 2023-01-19T21:36:23.000Z (about 3 years ago)
• Last Synced: 2025-09-09T08:24:52.446Z (7 months ago)
• Topics: federated-learning, optimization-algorithms, robust-optimization, robust-statistics, sgd
• Language: Roff
• Homepage:
• Size: 8.62 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Script To run: 

A. modify any of the configs / create a new config like the provided ones 

python3 -u optimization_driver.py --conf configs/hobbes_config.yaml --dir result_dumps/client_sampling/fmnist/lenet/ --o osgd_50 | tee ./result_dumps/client_sampling/fmnist/lenet/osgd_50.log