HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients
Federated Learning Library
An implementation of efficient federated learning algorithms for heterogeneous clients
[ICLR 2021] HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
152 stars
3 watching
33 forks
Language: Python
last commit: over 1 year ago deep-learningdistributed-machine-learningfederated-learningmodel-compression
Related projects:
| Repository | Description | Stars |
|---|---|---|
| diaoenmao/semifl-semi-supervised-federated-learning-for-unlabeled-clients-with-alternate-training | An implementation of semi-supervised federated learning for improving the performance of a server using distributed clients with unlabeled data | 34 |
 hypervoyager/pfl | An implementation of heterogeneous federated learning with parallel edge and server computation | 16 |
 yuetan031/fedproto | An implementation of federated learning with prototype-based methods across heterogeneous clients | 133 |
 omarfoq/fedem | Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. | 154 |
 pengyang7881187/fedrl | Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data | 54 |
 maxencenoble/differential-privacy-for-heterogeneous-federated-learning | An algorithm for balancing utility and privacy in federated learning on heterogeneous data | 59 |
 aiot-mlsys-lab/fedrolex | An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources. | 61 |
 xiyuanyang45/dynamicpfl | A method for personalizing machine learning models in federated learning settings with adaptive differential privacy to improve performance and robustness | 51 |
 litian96/ditto | A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems. | 137 |
 yutong-dai/fednh | An implementation of a federated learning framework for handling data heterogeneity in decentralized settings | 38 |
 haoyuzhao123/soteriafl | Numerical experiments for private federated learning with communication compression algorithms | 7 |
 ibm/federated-learning-lib | A framework for collaborative distributed machine learning in enterprise environments. | 499 |
 bytedance/feddecorr | Provides an implementation of various heterogeneous federated learning methods and datasets to mitigate dimensional collapse in distributed machine learning | 63 |
 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 |
 lins-lab/fedbr | An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data | 25 |