DaFKD2023
Federated distillation framework
A framework for achieving domain-aware knowledge distillation in federated learning environments.
Code for CVPR2023 DaFKD : Domain-aware Federated Knowledge Distillation
26 stars
1 watching
4 forks
Language: Python
last commit: over 1 year ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 diogenes0319/fedmd_clean | An implementation of a heterogenous federated learning framework using model distillation. | 149 |
 haozzh/fedcr | Evaluates various methods for federated learning on different models and tasks. | 18 |
 rong-dai/dispfl | An implementation of a personalized federated learning framework with decentralized sparse training and peer-to-peer communication protocol. | 72 |
 litian96/ditto | A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems. | 137 |
 bytedance/feddecorr | An implementation of a federated learning method to mitigate dimensional collapse in heterogeneous networks | 64 |
 jiayunz/fedalign | Develops an alignment framework for federated learning with non-identical client class sets | 4 |
 fangxiuwen/robust_fl | An implementation of a robust federated learning framework for handling noisy and heterogeneous clients in machine learning. | 43 |
 wenkehuang/fccl | A framework for tackling heterogeneity and catastrophic forgetting in federated learning by leveraging cross-correlation and similarity learning | 97 |
 yutong-dai/fednh | An implementation of a federated learning framework for handling data heterogeneity in decentralized settings | 38 |
 jinheonbaek/fed-pub | Personalized Subgraph Federated Learning framework for distributed machine learning | 44 |
 hypervoyager/pfl | An implementation of heterogeneous federated learning with parallel edge and server computation | 17 |
 cuis15/fcfl | An implementation of Fair and Consistent Federated Learning using Python. | 20 |
 jichan3751/ifca | A framework for decentralized collaborative learning across multiple clusters with efficient communication and data management strategies. | 105 |
 desternylin/perfed | An implementation of various federated learning algorithms with a focus on communication efficiency, robustness, and fairness. | 15 |
 vothanhvinh/causalrff | This project develops an adaptive kernel approach to federated learning of heterogeneous causal effects. | 1 |