FedOV

Federated Learning Framework

Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models.

Towards Addressing Label Skews in One-Shot Federated Learning (ICLR 2023)

GitHub

16 stars
2 watching
3 forks
Language: Python
last commit: about 1 year ago

Related projects:

Repository Description Stars
xtra-computing/fedsim A framework that enables federated learning across multiple datasets while optimizing model performance with record similarities. 24
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
xtra-computing/fedtree A system for distributed machine learning using tree-based models with secure aggregation and differential privacy features. 145
mediabrain-sjtu/fedgela An implementation of federated learning with bilateral curation for partially class-disjoint data 10
ibm/federated-learning-lib A framework for collaborative distributed machine learning in enterprise environments. 500
aiot-mlsys-lab/fedrolex An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources. 60
lxcnju/fedrepo An open-source repository implementing various federated learning algorithms with source code for multiple deep learning applications. 175
hongyouc/fed-rod Develops a framework to balance competing goals in federated learning by decoupling generic and personalized prediction tasks. 14
xmed-lab/rscfed This project presents a federated semi-supervised learning approach to improve model performance on multiple datasets by leveraging random sampling consensus. 46
haozzh/fedcr Evaluates various methods for federated learning on different models and tasks. 18
dawenzi098/sfl-structural-federated-learning A Python implementation of Personalized Federated Learning with Graph using PyTorch. 50
omarfoq/fedem Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. 155
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
scaleoutsystems/fedn An open source federated learning framework designed to be secure, scalable and easy-to-use for enterprise environments 144
litian96/ditto A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems. 137