FedRBN
Robustness Sharing
An implementation of Federated Robustness Propagation in PyTorch to share robustness across heterogeneous federated learning users.
[AAAI'23] Federated Robustness Propagation: Sharing Robustness in Heterogeneous Federated Learning
26 stars
4 watching
2 forks
Language: Python
last commit: almost 2 years ago aaaifederated-learningrobustnesstransfer-learning
Related projects:
| Repository | Description | Stars |
|---|---|---|
| illidanlab/foster | This project develops an approach to improve out-of-distribution detection in federated learning by leveraging data heterogeneity | 18 |
| illidanlab/splitmix | An algorithm for distributed learning with flexible model customization during training and testing | 40 |
 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 |
 pengyang7881187/fedrl | Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data | 56 |
 fangxiuwen/robust_fl | An implementation of a robust federated learning framework for handling noisy and heterogeneous clients in machine learning. | 43 |
 zfancy/sfat | Combating heterogeneity in federated learning by combining adversarial training with client-wise slack during aggregation | 28 |
 yamingguo98/fediir | An implementation of a federated learning algorithm that generalizes to out-of-distribution scenarios using implicit invariant relationships | 10 |
 lyn1874/fedpvr | An implementation of a federated learning algorithm for handling heterogeneous data | 6 |
 idanachituve/pfedgp | An implementation of Personalized Federated Learning with Gaussian Processes using Python. | 32 |
 yflyl613/fedrec | A PyTorch implementation of an attack and defense mechanism against Federated Recommendation Systems | 21 |
 litian96/fair_flearn | This project develops and evaluates algorithms for fair resource allocation in federated learning, aiming to promote more inclusive AI systems. | 244 |
 zhenqincn/fedapen | An implementation of cross-silo federated learning with adaptability to statistical heterogeneity | 12 |
 tmlr-group/fedfed | An approach to mitigating data heterogeneity in federated learning by sharing partial features of the data. | 17 |
 ai-secure/crfl | This project presents a framework for robust federated learning against backdoor attacks. | 71 |
 hendrycks/robustness | Evaluates and benchmarks the robustness of deep learning models to various corruptions and perturbations in computer vision tasks. | 1,030 |