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Sever: A Robust Meta-Algorithm for Stochastic Optimization

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Sever: A Robust Meta-Algorithm for Stochastic Optimization

refer to branch Sever

The official Matlab code can be found at https://github.com/hoonose/sever.

We adopt NumPy to reproduce a SVM classification defense algorithm.

You can also use the MinPy to further accelerate this algorithm, that is, just replace

    "import numpy as np " By

    "import MinPy.numpy as np" !

Details

 **For all image data, we adopt Resnet50 pretrained with imagenet to extract 1000-d features and fix and feed to the downstream svm classification defense.** 
for age and lfw data, the epsilon is set to 0.01, while for food, set epsilon as 0.05.

How to run

You should run the code like the following format:
`python3 defense.py --dataset dataname --flip_type method_name --flip_ratio int_number --optim SGD --num_round 2 --num_epoch 3 --device cuda:0` 

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