ZexiLee / ICML-2023-FedLAW

The is the official implementation of ICML 2023 paper "Revisiting Weighted Aggregation in Federated Learning with Neural Networks".

Date Created 2023-06-12 (about a year ago)

Commits 11 (last one about a year ago)

Stargazers 52 (0 this week)

Watchers 3 (0 this week)

Forks 7

License mit

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RepositoryStats indexes 595,856 repositories, of these ZexiLee/ICML-2023-FedLAW is ranked #457,315 (23rd percentile) for total stargazers, and #427,587 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #87,712/119,431.

ZexiLee/ICML-2023-FedLAW is also tagged with popular topics, for these it's ranked: deep-learning (#6,943/8512), federated-learning (#151/209), distributed-computing (#164/195)

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All Topics

model-fusion weight-decay deep-learning federated-learning distributed-computing

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11 commits on the default branch (main) since jan '22

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The only known language in this repository is Python

updated: 2024-12-20 @ 05:55am, id: 652519410 / R_kgDOJuSn8g