notears-admm

Federated learning algorithm

An implementation of Bayesian network structure learning with continuous optimization for federated learning.

Towards Federated Bayesian Network Structure Learning with Continuous Optimization

GitHub

10 stars
1 watching
1 forks
Language: Python
last commit: over 2 years ago

Related projects:

Repository Description Stars
sungwon-han/fedx An unsupervised federated learning algorithm that uses cross knowledge distillation to learn meaningful data representations from local and global levels. 68
lins-lab/fedbr An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data 25
yamingguo98/fediir An implementation of a federated learning algorithm that generalizes to out-of-distribution scenarios using implicit invariant relationships 10
hongliny/fedac-neurips20 Provides code for a federated learning algorithm to optimize machine learning models in a distributed setting. 14
mediabrain-sjtu/pfedgraph This project enables personalized federated learning with inferred collaboration graphs to improve the performance of machine learning models on non-IID (non-independent and identically distributed) datasets. 26
gaoliang13/feddc Federated learning algorithm that adapts to non-IID data by decoupling and correcting for local drift 81
optimization-ai/icml2023_fedxl An implementation of a federated learning algorithm for optimization problems with compositional pairwise risk optimization. 2
allenbeau/pfedbayes An implementation of personalized federated learning using variational Bayesian inference on the MNIST dataset 51
lx10077/fedavgpy The purpose of this project is to investigate the convergence of a federated learning algorithm on non-IID (non-identically and independently distributed) data. 254
omarfoq/fedem Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. 155
harliwu/fedamd This project presents an approach to federated learning with partial client participation by optimizing anchor selection for improving model accuracy and convergence. 2
atuannguyen/fedsr An implementation of a domain generalization method for federated learning using Python and PyTorch 26
idanachituve/pfedgp An implementation of Personalized Federated Learning with Gaussian Processes using Python. 32
xtra-computing/simfl A C++ implementation of a federated learning algorithm for decision trees, enabling multiple parties to jointly learn from their private data without sharing it. 18
lyn1874/fedpvr An implementation of a federated learning algorithm for handling heterogeneous data 6