thecheebo / Asynchronous-Federated-Learning-on-Hierarchical-ClustersLinks
CS525 Group research Paper. A central server uses network topology/clustering algorithm to assign clusters for workers. A special aggregator device is selected to enable hierarchical learning, leads to efficient communication between server and workers, while allowing heterogeneity.
☆18Updated 4 years ago
Alternatives and similar repositories for Asynchronous-Federated-Learning-on-Hierarchical-Clusters
Users that are interested in Asynchronous-Federated-Learning-on-Hierarchical-Clusters are comparing it to the libraries listed below
Sorting:
- Implementation of paper "Client-Edge-Cloud Hierarchical Federated Learning☆140Updated 5 years ago
- Asynchronous Federated Learning☆49Updated 2 years ago
- 完全去中心化联邦学习☆31Updated 2 years ago
- Implement FedAvg algorithm based on Tensorflow☆265Updated 5 years ago
- Source code for the paper "Asynchronous Federated Optimization"☆26Updated 3 years ago
- Active Client Selection for Federated Learning☆49Updated 2 years ago
- FLIS: Clustered Federated Learning via Inference Similarity for Non-IID Data Distribution☆40Updated 3 years ago
- A simulation framework for Federated Learning written in PyTorch☆209Updated 3 years ago
- ☆33Updated 3 years ago
- 通过阅读Communication-Efficient Learning of Deep Networks from Decentralized Data与Robust and Communication-Efficient Federated Learning from …☆40Updated 3 years ago
- A Proof-of-Stake (PoS) blockchain-based Federated Learning framework with a validation scheme robust against the distorted local model up…☆23Updated 2 years ago
- [IoTDI 2023/ML4IoT 2023] Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks☆40Updated 2 years ago
- A PyTorch implementation of "Communication-Efficient Learning of Deep Networks from Decentralized Data", AISTATS, 2017☆90Updated last year
- simulation of the asynchronous federated learning system of paper "Asynchronous Federated Optimization"☆23Updated 4 years ago
- On the Convergence of FedAvg on Non-IID Data☆274Updated 3 years ago
- Federated learning client selection☆22Updated 2 years ago
- 区块链+联邦学习+恶意检测算法☆30Updated 4 years ago
- ☆77Updated 2 years ago
- Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints☆185Updated 4 years ago
- Study of data imbalance and asynchronous aggregation algorithm on Federated Learning system (using PySyft)☆63Updated 2 years ago
- D-DQN Reinforcement Learning for device selection in Federated Learning☆42Updated 2 years ago
- Implementation of the ChainsFL.☆36Updated 4 years ago
- Implicit Model Specialization through DAG-based Decentralized Federated Learning☆20Updated 4 years ago
- Codes for the paper FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning☆46Updated 2 years ago
- Code for our paper "Byzantine-Resilient Federated Machine Learning via Over-the-Air Computation" (https://arxiv.org/abs/2105.10883).☆26Updated 4 years ago
- Standard federated learning implementations in FedLab and FL benchmarks.☆153Updated last year
- Democratize access to data, decentralize Artificial intelligence and enhance user privacy with Federated learning and Blockchain.☆193Updated 4 years ago
- PyTorch Federated Learning (easy to use and extend)☆295Updated 2 years ago
- Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge☆43Updated 3 years ago
- CMFL: Mitigating Communication Overhead for Federated Learning / PyTorch reimplementation.☆29Updated 6 years ago