feddistill
Code to reproduce the experiments of the ICLR25 paper "On the Byzantine-Resilience of Distillation-Based Federated Learning"
Science Score: 54.0%
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Keywords
Repository
Code to reproduce the experiments of the ICLR25 paper "On the Byzantine-Resilience of Distillation-Based Federated Learning"
Basic Info
- Host: GitHub
- Owner: ZIB-IOL
- Language: Python
- Default Branch: main
- Homepage: https://arxiv.org/abs/2402.12265
- Size: 93.8 KB
Statistics
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
[ICLR25] On the Byzantine-Resilience of Distillation-Based Federated Learning
Authors: Christophe Roux, Max Zimmer, Sebastian Pokutta
This repository contains the code to reproduce the experiments from the ICLR25 paper "On the Byzantine-Resilience of Distillation-Based Federated Learning". The code is based on PyTorch 1.9 and the experiment-tracking platform Weights & Biases.
Structure and Usage
Structure
Experiments are started from the following file:
main.py: Starts experiments using the dictionary format of Weights & Biases.
The rest of the project is structured as follows:
byzantine: Contains the attacks and defenses used in the paper.runners: Contains classes to control the training and collection of metrics.models: Contains all model architectures used.utilities.py: Contains useful auxiliary functions and classes.config.py: Configuration for the datasets used in the experiments.public_config.py: Contains the configuration for the public datasets.metrics.py: Contains the metrics used in the experiments.strategies.py: Contains the different strategies used, such as FedAVG and FedDistill.
Usage
Define the parameters in the main.py defaults-dictionary and run it with the --debug flag. Or, configure a sweep in Weights & Biases and run it from there (without the flag).
Citation
In case you find the paper or the implementation useful for your own research, please consider citing:
@inproceedings{roux2025on,
title={On the Byzantine-Resilience of Distillation-Based Federated Learning},
author={Christophe Roux and Max Zimmer and Sebastian Pokutta},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=of6EuHT7de}
}
Owner
- Name: IOL Lab
- Login: ZIB-IOL
- Kind: organization
- Location: Germany
- Website: https://iol.zib.de
- Repositories: 27
- Profile: https://github.com/ZIB-IOL
Working on optimization and learning at the intersection of mathematics and computer science
Citation (citation.bib)
@inproceedings{roux2025on,
title={On the Byzantine-Resilience of Distillation-Based Federated Learning},
author={Christophe Roux and Max Zimmer and Sebastian Pokutta},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=of6EuHT7de}
}
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