FedGELA
Data Fusion Tool
This project enables federated learning across partially class-disjoint data with curated bilateral curation.
[NeurIPS 2023]Federated Learning with Bilateral Curation for Partially Class-Disjoint Data
11 stars
1 watching
0 forks
Language: Python
last commit: over 1 year ago Related projects:
| Repository | Description | Stars |
|---|---|---|
| mediabrain-sjtu/feddisco | A federated learning framework with discrepancy-aware collaboration for decentralized data training | 68 |
| 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 |
 xtra-computing/fedov | Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models. | 17 |
 litian96/ditto | A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems. | 138 |
 dawenzi098/sfl-structural-federated-learning | A Python implementation of Personalized Federated Learning with Graph using PyTorch. | 49 |
 sjtu-yc/federated-submodel-averaging | An implementation of federated submodel averaging (FedSubAvg) to enable collaborative learning across decentralized devices or users. | 7 |
 ibm/federated-learning-lib | A framework for collaborative distributed machine learning in enterprise environments. | 500 |
 bibikar/feddst | An implementation of federated learning with sparse training and readjustment mechanisms to reduce communication overhead while maintaining model performance. | 29 |
 chandra2thapa/splitfed-when-federated-learning-meets-split-learning | An implementation of federated learning and split learning techniques with PyTorch on the HAM10000 dataset | 134 |
 substra/substra | Enables the training and validation of machine learning models on distributed datasets in a secure and scalable manner. | 274 |
 jiayunz/fedalign | Develops an alignment framework for federated learning with non-identical client class sets | 4 |
 yuetan031/fedproto | An implementation of federated learning with prototype-based methods across heterogeneous clients | 134 |
 omarfoq/fedem | Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. | 157 |
 lins-lab/fedbr | An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data | 25 |
 diogenes0319/fedmd_clean | An implementation of a heterogenous federated learning framework using model distillation. | 150 |