Federated-Neural-Bandits
Decentralized algorithm
An implementation of a decentralized algorithm for online decision-making in multiple agents
Federated Neural Bandits (ICLR 2023)
3 stars
1 watching
0 forks
Language: Jupyter Notebook
last commit: over 1 year ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 zhuangdizhu/fedgen | An implementation of algorithms for decentralized machine learning in heterogeneous federated learning settings. | 239 |
 abhimanyudubey/private_federated_linear_bandits | An implementation of differentially private federated linear bandits algorithm for decentralized decision-making in multiple agents | 4 |
 sungwon-han/fedx | An unsupervised federated learning algorithm that uses cross knowledge distillation to learn meaningful data representations from local and global levels. | 68 |
| daizhongxiang/differentially-private-federated-bayesian-optimization | An implementation of differential privacy in federated Bayesian optimization with distributed exploration | 3 |
 zhenqincn/fedapen | An implementation of cross-silo federated learning with adaptability to statistical heterogeneity | 10 |
 ymjs-irfan/dp-fedsam | This repository provides an implementation of a differentially private federated learning algorithm designed to improve the robustness and performance of federated machine learning systems. | 41 |
 xiyuanyang45/dynamicpfl | A method for personalizing machine learning models in federated learning settings with adaptive differential privacy to improve performance and robustness | 51 |
 gaoliang13/feddc | Federated learning algorithm that adapts to non-IID data by decoupling and correcting for local drift | 79 |
 xjiajiahao/federated-minimax | A framework for developing and testing decentralized machine learning algorithms | 2 |
 shengroup/pf_mab | An implementation of Federated Multi-Armed Bandits with Personalization using Python and Jupyter Notebook. | 6 |
 baowenxuan/fedcollab | An algorithm that optimizes collaboration in federated learning by clustering clients into non-overlapping coalitions based on data quantity and pairwise distribution distances. | 16 |
 yutong-dai/fednh | An implementation of a federated learning framework for handling data heterogeneity in decentralized settings | 38 |
 ignavierng/notears-admm | An implementation of Bayesian network structure learning with continuous optimization for federated learning. | 10 |
 yamingguo98/fediir | An implementation of a federated learning algorithm that generalizes to out-of-distribution scenarios using implicit invariant relationships | 9 |
 yh-yao/fedgcn | A software framework for training graph neural networks in a decentralized, federated learning setting | 59 |