scale-fl
Federated learner
An adaptive federated learning framework for heterogeneous clients with resource constraints.
Code for ScaleFL
30 stars
4 watching
1 forks
Language: Python
last commit: almost 2 years ago Related projects:
Repository | Description | Stars |
---|---|---|
| A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems. | 138 |
| An open source federated learning framework designed to be secure, scalable and easy-to-use for enterprise environments | 145 |
| An implementation of Fair and Consistent Federated Learning using Python. | 20 |
| Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models. | 17 |
| Enables the training and validation of machine learning models on distributed datasets in a secure and scalable manner. | 274 |
| A federated learning framework with discrepancy-aware collaboration for decentralized data training | 68 |
| A framework for collaborative learning across multiple tasks and datasets in a distributed manner | 130 |
| An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources. | 61 |
| A federated learning platform with tools and datasets for scalable and extensible machine learning experimentation | 390 |
| A Python implementation of Personalized Federated Learning with Graph using PyTorch. | 49 |
| Evaluates various methods for federated learning on different models and tasks. | 19 |
| An implementation of a heterogenous federated learning framework using model distillation. | 150 |
| This project enables federated learning across partially class-disjoint data with curated bilateral curation. | 11 |
| An implementation of a federated learning algorithm for handling heterogeneous data | 6 |
| An implementation of a personalized federated learning framework with decentralized sparse training and peer-to-peer communication protocol. | 72 |