Differential-Privacy-for-Heterogeneous-Federated-Learning

Federated Learning Algorithm

An algorithm for balancing utility and privacy in federated learning on heterogeneous data

Differentially Private Federated Learning on Heterogeneous Data

GitHub

59 stars
1 watching
10 forks
Language: Python
last commit: over 4 years ago

Related projects:

RepositoryDescriptionStars
diaoenmao/heterofl-computation-and-communication-efficient-federated-learning-for-heterogeneous-clientsAn implementation of efficient federated learning algorithms for heterogeneous clients155
xiyuanyang45/dynamicpflA method for personalizing machine learning models in federated learning settings with adaptive differential privacy to improve performance and robustness57
omarfoq/fedemDevelops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions.157
sap-samples/machine-learning-diff-private-federated-learningSimulates a federated learning setting to preserve individual data privacy365
ignavierng/notears-admmAn implementation of Bayesian network structure learning with continuous optimization for federated learning.10
shenzebang/centaur-privacy-federated-representation-learningA framework for Federated Learning with Differential Privacy using PyTorch13
xtra-computing/simflA C++ implementation of a federated learning algorithm for decision trees, enabling multiple parties to jointly learn from their private data without sharing it.18
mmendiet/fedalignA federated learning framework designed to mitigate data heterogeneity in distributed learning settings.55
pengyang7881187/fedrlEnabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data56
mingruiliu-ml-lab/episodeAn algorithm for Federated Learning with heterogeneous data, designed to optimize deep neural networks and improve performance2
lyn1874/fedpvrAn implementation of a federated learning algorithm for handling heterogeneous data6
zfancy/sfatCombating heterogeneity in federated learning by combining adversarial training with client-wise slack during aggregation28
hmgxr128/mifa_codeAn implementation of Fast Federated Learning under device unavailability for minimizing latency and achieving optimal convergence rates9
kenziyuliu/private-cross-silo-flThis repository provides an implementation of a cross-silo federated learning framework with differential privacy mechanisms.25
lins-lab/fedbrAn implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data25