fedl2p

Personalized Learning Model Trainer

This project enables personalized learning models by collaborating on learning the best strategy for each client

[NeurIPS'23] FedL2P: Federated Learning to Personalize

GitHub

19 stars
2 watching
3 forks
Language: Python
last commit: 5 months ago

Related projects:

Repository Description Stars
dawenzi098/sfl-structural-federated-learning A Python implementation of Personalized Federated Learning with Graph using PyTorch. 50
tsingz0/fedcp A framework that separates feature information from data in federated learning to enable personalized models. 26
krishnap25/fl_partial_personalization A framework for federated learning with partial model personalization 2
yuetan031/fedproto An implementation of federated learning with prototype-based methods across heterogeneous clients 133
xiyuanyang45/dynamicpfl A method for personalizing machine learning models in federated learning settings with adaptive differential privacy to improve performance and robustness 51
pengyang7881187/fedrl Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data 54
allenbeau/pfedbayes An implementation of personalized federated learning using variational Bayesian inference on the MNIST dataset 50
gwenlegate/guidinglastlayerflpretrain Investigates transfer learning in federated learning by guiding the last layer with pre-trained models 7
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
zhenqincn/fedapen An implementation of cross-silo federated learning with adaptability to statistical heterogeneity 10
lins-lab/fedthe Improves machine learning models for personalized performance under evolving test distributions in distributed environments 53
hongliny/fedac-neurips20 Provides code for a federated learning algorithm to optimize machine learning models in a distributed setting. 14
lyn1874/fedpvr An implementation of a federated learning algorithm for handling heterogeneous data 6
lunanbit/fedul This project presents an approach to federated learning that leverages unsupervised techniques to adapt models to unlabeled data without requiring labels. 33
aiot-mlsys-lab/fedrolex An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources. 61