066-incentive-aware-federated-learning-with-training-time-model-rewards

https://github.com/szu-advtech-2024/066-incentive-aware-federated-learning-with-training-time-model-rewards

Science Score: 31.0%

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CITATION.cff file
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Host: GitHub
Owner: SZU-AdvTech-2024
Default Branch: main
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Created over 1 year ago · Last pushed over 1 year ago

Metadata Files

Citation

https://github.com/SZU-AdvTech-2024/066-Incentive-Aware-Federated-Learning-with-Training-Time-Model-Rewards/blob/main/

## Requirements

To install requirements:
```setup
conda env create -f environment.yml
```

## Run IAFL experiments

At the beginning of the `iafl.py` file, there are descriptions for the options required to run the code.

We give one example here:
```bash
python iafl.py --config ./config/cifar/iafl/cifar_iafl.yaml
```

Owner

Name: SZU-AdvTech-2024
Login: SZU-AdvTech-2024
Kind: organization

Repositories: 1
Profile: https://github.com/SZU-AdvTech-2024

Citation (citation.txt)

@inproceedings{REPO066,
    author = "Wu, Zhaoxuan and Amiri, Mohammad Mohammadi and Raskar, Ramesh and Low, Bryan Kian Hsiang",
    booktitle = "The Twelfth International Conference on Learning Representations",
    title = "{Incentive-Aware Federated Learning with Training-Time Model Rewards}",
    url = "https://openreview.net/forum?id=FlY7WQ2hWS",
    year = "2024"
}

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