perfed

Federated learning frameworks

An implementation of various federated learning algorithms with a focus on communication efficiency, robustness, and fairness.

GitHub

15 stars
1 watching
1 forks
Language: Python
last commit: 9 months ago

Related projects:

Repository Description Stars
litian96/ditto A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems. 137
bdemo/pfedbred_public A project that proposes a novel federated learning approach to address the issue of incomplete information in personalized machine learning models 8
ibm/federated-learning-lib A framework for collaborative distributed machine learning in enterprise environments. 499
lxcnju/fedrepo An open-source repository implementing various federated learning algorithms with source code for multiple deep learning applications. 174
rong-dai/dispfl An implementation of a personalized federated learning framework with decentralized sparse training and peer-to-peer communication protocol. 68
diogenes0319/fedmd_clean An implementation of a heterogenous federated learning framework using model distillation. 149
cuis15/fcfl An implementation of Fair and Consistent Federated Learning using Python. 20
charliedinh/pfedme An implementation of Personalized Federated Learning with Moreau Envelopes and related algorithms using PyTorch for research and experimentation. 289
fangxiuwen/robust_fl An implementation of a robust federated learning framework for handling noisy and heterogeneous clients in machine learning. 41
xtra-computing/fedsim A framework that enables federated learning across multiple datasets while optimizing model performance with record similarities. 24
codepothunter/fednp A framework for non-IID federated learning via neural propagation 6
mediabrain-sjtu/fedgela Federated learning algorithm designed to handle partially class-disjoint data by utilizing bilateral curation and Dirichlet partitioning. 10
xtra-computing/fedov Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models. 14
omarfoq/fedem Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. 154
bytedance/feddecorr Provides an implementation of various heterogeneous federated learning methods and datasets to mitigate dimensional collapse in distributed machine learning 63