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Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)

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I have some problems when i am trying to reproduce the experiment results in this paper. I pull the source code and run it with params.yaml after setting is_poison=True and...

Even with "is_poison"=false, the accuracy is only about 10%. When "is_poison"=true and batch_size=264, I get the results as follows: When there are adversaries, accuracy of backdoor is about 100%,accuracy without...

when i run **_python training.py --params utils/params.yaml_**, raised a error :

It seems to me that poison_dataset() didn't poison the data, it just sampled 64 images 200 times and required them not to be images from "posion_image" and "poison_images_test". But what...

I would like to run your code. Could you tell me which Python packages and their respective versions are required to execute it? ![ecd54f7de7223d9d22995ad7e8c461a](https://github.com/ebagdasa/backdoor_federated_learning/assets/147410452/9c8871b8-b678-4bc6-ae80-d447fed15e23)

不同版本的pytorch会对实验结果有影响吗

Does anyone have this corpus database?Could you please send me a copy? Thx. My email address is: [[email protected]](mailto:[email protected])

Bumps [torch](https://github.com/pytorch/pytorch) from 1.0 to 2.2.0. Release notes Sourced from torch's releases. PyTorch 2.2: FlashAttention-v2, AOTInductor PyTorch 2.2 Release Notes Highlights Backwards Incompatible Changes Deprecations New Features Improvements Bug fixes...

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