This hub stores the code for paper Byzantine-Resilient Distributed Finite-Sum Optimization over Networks (short version) and Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks (full version, which can be seen in Full.pdf). The code should be run in the jupyter notebook.
- python 3.7.4
- pytorch 1.2.0
- matplotlib 3.1.1
The main programs can be found in the following files:
- Byrd_SAGA_torch_LinearRegression.ipynb: The experiment on linear regression.
- Byrd_SAGA_torch_ANN.ipynb: The experiment on neural network.
- draw.ipynb: The script to draw picture.
Download the dataset to the file folder ./dataset and create a file folder named ./cache. The experiment output will be stored in ./cache.
- ijcnn1/covtype: https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/
- MNIST: http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz
We would like to thanks to Runhua Wang, SYSU, for helping us to review and improve our code.