c-gabri / Federated-Learning-PyTorch

PyTorch implementation of Federated Learning algorithms FedSGD, FedAvg, FedAvgM, FedIR, FedVC, FedProx and standard SGD, applied to visual classification. Client distributions are synthesized with arbitrary non-identicalness and imbalance (Dirichlet priors). Client systems can be arbitrarily heterogeneous. Several mobile-friendly models are provided

Date Created 2022-01-05 (2 years ago)

Commits 204 (last one 2 years ago)

Stargazers 69 (0 this week)

Watchers 2 (0 this week)

Forks 14

License gpl-3.0

Ranking

RepositoryStats indexes 595,856 repositories, of these c-gabri/Federated-Learning-PyTorch is ranked #378,426 (36th percentile) for total stargazers, and #485,301 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #71,838/119,431.

c-gabri/Federated-Learning-PyTorch is also tagged with popular topics, for these it's ranked: pytorch (#4,270/6025), classification (#370/543), federated-learning (#122/209)

Other Information

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All Topics

sgd fedir fedvc fedavg fedsgd fedavgm fedprox non-iid pytorch imbalance heterogeneity classification federated-learning

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137 commits on the default branch (master) since jan '22

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updated: 2024-12-07 @ 04:13am, id: 444874361 / R_kgDOGoQ-eQ