machine-learning-diff-private-federated-learning

Federated Learning Simulator

Simulates a federated learning setting to preserve individual data privacy

Simulate a federated setting and run differentially private federated learning.

GitHub

360 stars
16 watching
94 forks
Language: Python
last commit: 4 months ago
differential-privacyfederated-learningmachine-learningsamplesample-codesecurity

Related projects:

Repository Description Stars
omarfoq/fedem Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. 154
maxencenoble/differential-privacy-for-heterogeneous-federated-learning An algorithm for balancing utility and privacy in federated learning on heterogeneous data 59
microsoft/msrflute A platform for conducting high-performance federated learning simulations in Python. 185
shams-sam/fedoptim An open-source project exploring Federated Learning model updates and their rank structure using data from various datasets. 13
shenzebang/centaur-privacy-federated-representation-learning A framework for Federated Learning with Differential Privacy using PyTorch 13
jeremy313/soteria An implementation of a defense against model inversion attacks in federated learning 55
dcalab-unipv/turning-privacy-preserving-mechanisms-against-federated-learning This project presents an attack on federated learning systems to compromise their privacy-preserving mechanisms. 8
lyn1874/fedpvr An implementation of a federated learning algorithm for handling heterogeneous data 6
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
kenziyuliu/private-cross-silo-fl This repository provides an implementation of a cross-silo federated learning framework with differential privacy mechanisms. 25
dawenzi098/sfl-structural-federated-learning A Python implementation of Personalized Federated Learning with Graph using PyTorch. 50
xiyuanyang45/dynamicpfl A method for personalizing machine learning models in federated learning settings with adaptive differential privacy to improve performance and robustness 51
lins-lab/fedbr An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data 25
google/fedjax A library that provides an easy-to-use framework for simulating federated learning algorithms 252
xtra-computing/fedov Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models. 14