The source code for FedMut: Generalized Federated Learning via Stochastic Mutation (Accepted by AAAI2024)

https://ojs.aaai.org/index.php/AAAI/article/view/29146

• Python 3.7
• PyTorch

--dataset <dataset name>

We can set ‘cifar10’, ‘cifar100’ and ‘femnist’ for CIFAR-10, CIFAR-100, and FEMNIST.

--num_classes <number>

Set the number of classes Set 10 for CIFAR-10

Set 20 for CIFAR-100

Set 62 for FEMNIST

--num_channels <number>

Set the number of channels of data Set 3 for CIFAR-10 and CIFAR-100. Set 1 for FEMNIST.

--iid <0 or 1>

0 – set non-iid 1 – set iid

--data_beta <𝛼>

Set the 𝛂 for the Dirichlet distribution

--generate_data <0 or 1>

0 – use the existing configuration of 𝑫𝒊𝒓(𝜶) 1 – generate a new configuration of 𝑫𝒊𝒓(𝜶)

--epochs <number of rounds>

Set the number of training rounds.

-- algorithm <baseline name>

Set the baseline name:

• FedMut
• FedAvg
• FedProx
• FedGen
• ClustererSampling

-- radius <float>

Set the range of mutation for FedMut

-- mut_acc_rate <float>

Set the acceleration rate for FedMut

Please use the tool as follows to generate the figure of loss-landscape：

https://github.com/tomgoldstein/loss-landscape

@inproceedings{hu2024fedmut,
  title={FedMut: Generalized Federated Learning via Stochastic Mutation},
  author={Hu, Ming and Cao, Yue and Li, Anran and Li, Zhiming and Liu, Chengwei and Li, Tianlin and Chen, Mingsong and Liu, Yang},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={38},
  number={11},
  pages={12528--12537},
  year={2024}
}