VHL
FL defense tool
A toolkit for federated learning with a focus on defending against data heterogeneity
ICML2022: Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
40 stars
2 watching
12 forks
Language: Python
last commit: almost 4 years agoRelated projects:
| Repository | Description | Stars |
|---|---|---|
 jeremy313/fl-wbc | A defense mechanism against model poisoning attacks in federated learning | 37 |
 git-disl/lockdown | A backdoor defense system for federated learning, designed to protect against data poisoning attacks by isolating subspace training and aggregating models with robust consensus fusion. | 18 |
 conditionwang/fcil | A PyTorch implementation of Federated Class-Incremental Learning for Continual Learning in Computer Vision | 102 |
| jeremy313/soteria | An implementation of a defense against model inversion attacks in federated learning | 55 |
 lyn1874/fedpvr | An implementation of a federated learning algorithm for handling heterogeneous data | 6 |
 deu30303/feddefender | A PyTorch implementation of an attack-tolerant federated learning system to train robust local models against malicious attacks from adversaries. | 10 |
 zfancy/sfat | Combating heterogeneity in federated learning by combining adversarial training with client-wise slack during aggregation | 28 |
 pengyang7881187/fedrl | Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data | 56 |
 hypervoyager/pfl | An implementation of heterogeneous federated learning with parallel edge and server computation | 17 |
 hfzhang31/a3fl | A framework for attacking federated learning systems with adaptive backdoor attacks | 23 |
 aiot-mlsys-lab/fedrolex | An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources. | 61 |
 zju-diver/shapleyfl-robust-federated-learning-based-on-shapley-value | An implementation of a robust federated learning method based on Shapley value to defend against various data and model poisoning attacks | 19 |
 gwenlegate/guidinglastlayerflpretrain | Investigates transfer learning in federated learning by guiding the last layer with pre-trained models | 7 |
 shenzebang/federated-learning-pytorch | A PyTorch-based framework for Federated Learning experiments | 40 |
 haozzh/fedcr | Evaluates various methods for federated learning on different models and tasks. | 19 |