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.