Numerical experiments for BEER
December 30, 2022 ยท View on GitHub
This repository contains numerical experiments for "BEER: Fast O(1/T) Rate for Decentralized Nonconvex Optimization with Communication Compression" [PDF].
If you find this repo useful, please cite our paper
@article{zhao2022beer,
title={BEER: Fast O (1/T) Rate for Decentralized Nonconvex Optimization with Communication Compression},
author={Zhao, Haoyu and Li, Boyue and Li, Zhize and Richt{\'a}rik, Peter and Chi, Yuejie},
journal={Advances in Neural Information Processing Systems},
volume = {35},
year={2022}
}
1. Folder structure
-
beer/: framework for convolutional neural network experiments. -
experiments/experiments.ipynb: code for synthetic numerical experiments. -
experiments/mnist/: code and scripts for convolutional neural network experiments.
2. Installation
Please install [this package] first.
Then run pip install git+https://github.com/liboyue/beer.git to install this package.