mingkunyang

federated-learning

A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561

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

FedMA

Code for Federated Learning with Matched Averaging, ICLR 2020.

flower

Flower - A Friendly Federated Learning Framework

mingkunyang.github.io

starter-academic

🎓 Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify

Statistical-Learning-Method_Code

手写实现李航《统计学习方法》书中全部算法

FedTrans

[ICLR 2024] "FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning"

mingkunyang/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

mingkunyang/flower

Flower - A Friendly Federated Learning Framework

mingkunyang/FedMA

Code for Federated Learning with Matched Averaging, ICLR 2020.

mingkunyang/federated-learning

A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561

mingkunyang/mingkunyang.github.io

mingkunyang/starter-academic

🎓 Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify

mingkunyang/Statistical-Learning-Method_Code

手写实现李航《统计学习方法》书中全部算法