FedAMD
Federated Learning Algorithm
This project presents an approach to federated learning with partial client participation by optimizing anchor selection for improving model accuracy and convergence.
Official Repository for "Anchor Sampling for Federated Learning with Partial Client Participation"
2 stars
1 watching
1 forks
Language: Python
last commit: 8 months ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 pengyang7881187/fedrl | Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data | 54 |
 haozzh/fedcr | Evaluates various methods for federated learning on different models and tasks. | 17 |
 gaoliang13/feddc | Federated learning algorithm that adapts to non-IID data by decoupling and correcting for local drift | 79 |
 hongliny/fedac-neurips20 | Provides code for a federated learning algorithm to optimize machine learning models in a distributed setting. | 14 |
 yamingguo98/fediir | An implementation of a federated learning algorithm that generalizes to out-of-distribution scenarios using implicit invariant relationships | 9 |
 omarfoq/fedem | Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. | 154 |
 lunanbit/fedul | This project presents an approach to federated learning that leverages unsupervised techniques to adapt models to unlabeled data without requiring labels. | 33 |
 lyn1874/fedpvr | An implementation of a federated learning algorithm for handling heterogeneous data | 6 |
 wyjeong/fedmatch | A project implementing Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning | 79 |
 lins-lab/fedbr | An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data | 25 |
 ignavierng/notears-admm | An implementation of Bayesian network structure learning with continuous optimization for federated learning. | 10 |
 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 |
 litian96/fair_flearn | This project develops and evaluates algorithms for fair resource allocation in federated learning, aiming to promote more inclusive AI systems. | 243 |
 sungwon-han/fedx | An unsupervised federated learning algorithm that uses cross knowledge distillation to learn meaningful data representations from local and global levels. | 68 |
 jiayunz/fedalign | Develops an alignment framework for federated learning with non-identical client class sets | 4 |