DisTrans
Federated learning enhancer
Improves federated learning models by addressing data heterogeneity through distributional transformation
5 stars
1 watching
0 forks
Language: Python
last commit: about 4 years agoRelated projects:
| Repository | Description | Stars |
|---|---|---|
 mediabrain-sjtu/fedgela | This project enables federated learning across partially class-disjoint data with curated bilateral curation. | 11 |
 lyn1874/fedpvr | An implementation of a federated learning algorithm for handling heterogeneous data | 6 |
 harliwu/fedamd | This project presents an approach to federated learning with partial client participation by optimizing anchor selection for improving model accuracy and convergence. | 2 |
| 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 |
 hongliny/fedac-neurips20 | Provides code for a federated learning algorithm to optimize machine learning models in a distributed setting. | 14 |
 wyjeong/fedmatch | A project implementing Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning | 80 |
 diogenes0319/fedmd_clean | An implementation of a heterogenous federated learning framework using model distillation. | 150 |
 divyansh03/fedexp | An implementation of a federated averaging algorithm with an extrapolation approach to speed up distributed machine learning training on client-held data. | 9 |
 lins-lab/fedbr | An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data | 25 |
| mediabrain-sjtu/feddisco | A federated learning framework with discrepancy-aware collaboration for decentralized data training | 68 |
 haozzh/fedcr | Evaluates various methods for federated learning on different models and tasks. | 19 |
 pengyang7881187/fedrl | Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data | 56 |
 liruichenspace/fedfusion | An implementation of federated learning with data-agnostic distribution fusion using PyTorch. | 8 |
 chandra2thapa/splitfed-when-federated-learning-meets-split-learning | An implementation of federated learning and split learning techniques with PyTorch on the HAM10000 dataset | 134 |
 diaoenmao/heterofl-computation-and-communication-efficient-federated-learning-for-heterogeneous-clients | An implementation of efficient federated learning algorithms for heterogeneous clients | 155 |