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 3 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☆129Updated 5 years ago
- 完全去中心化联邦学习☆28Updated last year
- Active Client Selection for Federated Learning☆47Updated 2 years ago
- FLIS: Clustered Federated Learning via Inference Similarity for Non-IID Data Distribution☆39Updated 2 years ago
- Source code for the paper "Asynchronous Federated Optimization"☆25Updated 2 years ago
- Implement FedAvg algorithm based on Tensorflow☆253Updated 4 years ago
- Asynchronous Federated Learning☆46Updated 2 years ago
- [IoTDI 2023/ML4IoT 2023] Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks☆37Updated 2 years ago
- ☆30Updated 3 years ago
- A PyTorch implementation of "Communication-Efficient Learning of Deep Networks from Decentralized Data", AISTATS, 2017☆84Updated 11 months ago
- A Proof-of-Stake (PoS) blockchain-based Federated Learning framework with a validation scheme robust against the distorted local model up…☆22Updated last year
- A simulation framework for Federated Learning written in PyTorch☆207Updated 3 years ago
- 通过阅读Communication-Efficient Learning of Deep Networks from Decentralized Data与Robust and Communication-Efficient Federated Learning from …☆38Updated 2 years ago
- On the Convergence of FedAvg on Non-IID Data☆266Updated 2 years ago
- Codes for the paper FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning☆45Updated 2 years ago
- This is a platform containing the datasets and federated learning algorithms in IoT environments.☆65Updated 7 months ago
- Code for our paper "Byzantine-Resilient Federated Machine Learning via Over-the-Air Computation" (https://arxiv.org/abs/2105.10883).☆25Updated 4 years ago
- Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints☆174Updated 4 years ago
- Implicit Model Specialization through DAG-based Decentralized Federated Learning☆19Updated 3 years ago
- simulation of the asynchronous federated learning system of paper "Asynchronous Federated Optimization"☆23Updated 3 years ago
- Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge☆40Updated 3 years ago
- Federated learning client selection☆18Updated 2 years ago
- [ICML 2022] "DisPFL: Towards Communication-Efficient Personalized Federated learning via Decentralized Sparse Training"☆80Updated 3 years ago
- Decentralized federated learning of deep neural networks on non-iid data☆45Updated 3 years ago
- CMFL: Mitigating Communication Overhead for Federated Learning / PyTorch reimplementation.☆29Updated 5 years ago
- FlexCFL: A clustered federated learning framework based on TF2.0. Support frameworks: FlexCFL, FedGroup, FedAvg, IFCA, FeSEM, et al.☆49Updated 2 years ago
- DeceFL: A Principled Decentralized Federated Learning Framework☆28Updated 2 years ago
- [ACM MobiCom 2022] "PyramidFL: Fine-grained Data and System Heterogeneity-aware Client Selection for Efficient Federated Learning" by Che…☆71Updated 2 years ago
- Three implementations of FedAvg: numpy, pytorch and tensorflow federated.☆43Updated 3 years ago
- Releasing the source code Version1.☆165Updated 3 years ago