Sofianebouaziz1 / FLASH-RL
FLASH-RL (Federated Learning Addressing System and Static Heterogeneity using Reinforcement Learning) is a novel and effective strategy for client selection in Federated Learning using Reinforcement Learning to address heterogeneity problems.
☆36Updated 8 months ago
Alternatives and similar repositories for FLASH-RL:
Users that are interested in FLASH-RL are comparing it to the libraries listed below
- ☆11Updated 4 years ago
- Federated Reinforcement Learning project☆26Updated last year
- ☆12Updated last year
- Welcome to FLSim_V2, a PyTorch based federated Reinforcement learning simulation framework☆9Updated 2 years ago
- Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Preserving EdgeIoT☆28Updated 9 months ago
- Federated Learning for Energy-balanced Client Selection in Mobile Edge Computing☆35Updated 8 months ago
- Official code for "Federated Learning under Heterogeneous and Correlated Client Availability" (INFOCOM'23)☆28Updated 2 years ago
- This is a repository for the implementation of the paper "Green, Quantized Federated Learning over Wireless Networks: An Energy-Efficient…☆11Updated last year
- Migration of Edge-based Distributed Federated Learning☆23Updated 2 years ago
- Code for 'Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing', published in IEEE TPDS.☆89Updated 2 years ago
- Adaptive Offloading of Federated Learning on IoT Devices☆70Updated 2 years ago
- qiongwu86 / Asynchronous-Federated-Learning-Based-Mobility-aware-Caching-in-Vehicular-Edge-Computing☆76Updated last year
- A simulation of energy consumption of a federated learning system based on the non-orthogonal multiple access (NOMA) transmission protoco…☆25Updated 4 years ago
- ☆64Updated 3 years ago
- ☆17Updated last year
- Publication catalog for research on Federated RL (FRL).☆79Updated 3 years ago
- Code of "HSFL: Efficient and Privacy-Preserving Offloading for Split and Federated Learning in IoT Services" published on International C…☆15Updated last year
- ☆26Updated last year
- The code for the paper "Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation"☆29Updated 3 years ago
- In this work, we propose a novel formulation titled Federated Deep Q Networks (F-DQN) to perform distributed learning for Deep RL algorit…☆19Updated 4 years ago
- ☆21Updated last year
- Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge☆37Updated 2 years ago
- Active Client Selection for Federated Learning☆42Updated last year
- Federated Learning over Wireless Networks☆44Updated 3 years ago
- Federated learning client selection☆19Updated last year
- Code for the case study presented in "Making a Case for Federated Learning in the Internet of Vehicles and Intelligent Transportation Sys…☆24Updated 3 years ago
- D-DQN Reinforcement Learning for device selection in Federated Learning☆40Updated last year
- Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation☆31Updated 3 years ago
- code for NeurIPS2021 paper on Federated Reinforcement Learning with Byzantine Resilience☆89Updated last year
- hizircanbayram / FeDQN-A-Federated-Learning-Approach-for-Training-Reinforcement-Learning-Agent-of-Atari-GamesFeDQN is a federated pipeline for training reinforcement learning agent of atari game, the Pong, developed during my first semester at Is…☆24Updated 3 years ago