SyedUmaidAhmed / Federated-and-Split-Learning-on-Edge
This is the official implementation of Federated and Split Learning on multiple Raspberry Pi's. It is the demonstration of training the data on edge devices without having threat to security issues.
☆11Updated last year
Related projects ⓘ
Alternatives and complementary repositories for Federated-and-Split-Learning-on-Edge
- LotteryFL: Empower Edge Intelligence with Personalized and Communication-Efficient Federated Learning (2021 IEEE/ACM Symposium on Edge Co…☆38Updated last year
- This is the code repository for the following paper: "Model pruning enables efficient federated learning on edge devices".☆80Updated 2 years ago
- Official implementations for "Communication-Efficient Diffusion Strategy for Performance Improvement of Federated Learning with Non-IID D…☆20Updated 8 months ago
- Official implementation for paper "No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation", I…☆16Updated last year
- ☆23Updated 11 months ago
- ☆23Updated 3 years ago
- Official code for "Throughput-Optimal Topology Design for Cross-Silo Federated Learning" (NeurIPS'20)☆30Updated 2 years ago
- Code for ScaleFL☆29Updated last year
- Official Code for PACFL AAAI 2023☆37Updated last year
- Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity☆40Updated 3 years ago
- FLIS: Clustered Federated Learning via Inference Similarity for Non-IID Data Distribution☆32Updated 2 years ago
- Official code for "Federated Learning under Heterogeneous and Correlated Client Availability" (INFOCOM'23)☆27Updated last year
- Official Pytorch implementation of "Communication-Efficient Federated Learning with Compensated Overlap-FedAvg"☆23Updated 3 years ago
- [IoTDI 2023/ML4IoT 2023] Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks☆32Updated last year
- An implementation for "Federated Learning with Non-IID Data via Local Drift Decoupling and Correction"☆79Updated 2 years ago
- diaoenmao / HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients[ICLR 2021] HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients☆152Updated last year
- PyTorch implementation of: D. Shenaj, M. Toldo, A. Rigon and P. Zanuttigh, “Asynchronous Federated Continual Learning”, CVPR 2023 Worksho…☆23Updated last year
- Federated Dynamic Sparse Training☆29Updated 2 years ago
- Diverse Client Selection for Federated Learning via Submodular Maximization☆28Updated 2 years ago
- 关于簇联邦学习的一个小小的改进。自动确定簇个数,提高簇模型精度,缓解用户孤立的问题☆34Updated 2 years ago
- This repository implements FEDL using pytorch☆48Updated 4 years ago
- fully ready experiments☆32Updated 2 years ago
- FedGroup, A Clustered Federated Learning framework based on Tensorflow☆38Updated 2 years ago
- Decentralized federated learning of deep neural networks on non-iid data☆38Updated 2 years ago
- ☆30Updated 2 years ago
- inherit from https://github.com/iqua/flsim☆9Updated 4 years ago
- [NeurIPS 2022] "FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction" by Samiul Alam, Luyang Liu, Ming Yan,…☆61Updated 2 months ago
- Implementation of SCAFFOLD: Stochastic Controlled Averaging for Federated Learning☆62Updated last year
- [DMLR 2024] FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things☆49Updated 2 months ago
- An implementation of FedPAQ using different experimental parameters. We will be looking at different variations of how, r(number of clien…☆22Updated 3 years ago