DisPFL

Federated Learning Framework

An implementation of a personalized federated learning framework with decentralized sparse training and peer-to-peer communication protocol.

[ICML 2022] "DisPFL: Towards Communication-Efficient Personalized Federated learning via Decentralized Sparse Training"

GitHub

72 stars
2 watching
14 forks
Language: Python
last commit: over 2 years ago

Related projects:

Repository Description Stars
litian96/ditto A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems. 138
yutong-dai/fednh An implementation of a federated learning framework for handling data heterogeneity in decentralized settings 38
desternylin/perfed An implementation of various federated learning algorithms with a focus on communication efficiency, robustness, and fairness. 15
cuis15/fcfl An implementation of Fair and Consistent Federated Learning using Python. 20
fangxiuwen/robust_fl An implementation of a robust federated learning framework for handling noisy and heterogeneous clients in machine learning. 43
wenkehuang/fccl A framework for tackling heterogeneity and catastrophic forgetting in federated learning by leveraging cross-correlation and similarity learning 97
hypervoyager/pfl An implementation of heterogeneous federated learning with parallel edge and server computation 17
galaxylearning/gfl A decentralized federated learning framework based on blockchain and PyTorch. 243
ibm/federated-learning-lib A framework for collaborative distributed machine learning in enterprise environments. 500
securefederatedai/openfl A Python framework for collaborative machine learning without sharing sensitive data 738
diogenes0319/fedmd_clean An implementation of a heterogenous federated learning framework using model distillation. 150
xtra-computing/fedsim A framework that enables federated learning across multiple datasets while optimizing model performance with record similarities. 25
diaoenmao/semifl-semi-supervised-federated-learning-for-unlabeled-clients-with-alternate-training An implementation of semi-supervised federated learning for improving the performance of a server using distributed clients with unlabeled data 36
bytedance/feddecorr Implementation of various federated learning algorithms to mitigate dimensional collapse in heterogeneous federated learning environments 64
jinheonbaek/fed-pub Personalized Subgraph Federated Learning framework for distributed machine learning 45