yj4889 / yj4889-Optimized-Quantization-for-Convolutional-Deep-Neural-Networks-in-Federated-LearningLinks
Federated learning is a distributed learning method that trains a deep network on user devices without collecting data from central server. It is useful when the central server can’t collect data. However, the absence of data on central server means that deep network compression using data is not possible. Deep network compression is very import…
☆14Updated 5 years ago
Alternatives and similar repositories for yj4889-Optimized-Quantization-for-Convolutional-Deep-Neural-Networks-in-Federated-Learning
Users that are interested in yj4889-Optimized-Quantization-for-Convolutional-Deep-Neural-Networks-in-Federated-Learning are comparing it to the libraries listed below
Sorting:
- Multi-Stage Hybrid Federated Learning over Large-Scale Wireless Fog Networks☆17Updated 3 years ago
- Code Implemntion from the article Multi-Armed Bandit Based Client Schedulingfor Federated Learning☆17Updated 4 years ago
- ☆37Updated 2 years ago
- Code for Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence☆15Updated 4 years ago
- ☆11Updated 3 years ago
- Multiple Edge Servers Assignment for Local Device in Hierarchical Federated Learning☆20Updated 4 years ago
- Official implementations for "Communication-Efficient Diffusion Strategy for Performance Improvement of Federated Learning with Non-IID D…☆22Updated last year
- Official code for "Federated Learning under Heterogeneous and Correlated Client Availability" (INFOCOM'23)☆27Updated 2 years ago
- ☆11Updated 2 years ago
- Hao Jin, Yang Peng, Wenhao Yang, Shusen Wang and Zhihua Zhang. Federated Reinforcement Learning with Environment Heterogeneity. AISTATS, …☆61Updated 3 years ago
- Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection, backed by FedML, Inc.☆44Updated 3 years ago
- [NeurIPS2021] Federated Reinforcement Learning with Theoretical Guarantees. The repo contains code and experiments for our Federated Poli…☆98Updated 5 months ago
- Federated Learning over Wireless Networks☆46Updated 4 years ago
- Adaptive Offloading of Federated Learning on IoT Devices☆76Updated 2 years ago
- A PyTorch Implementation for experiements in paper: Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge.☆14Updated 2 years ago
- SFedChain: blockchain-based federated learning scheme for secure data sharing in distributed energy storage networks☆12Updated 3 years ago
- Migration of Edge-based Distributed Federated Learning☆25Updated 2 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…☆21Updated 4 years ago
- ☆11Updated 4 years ago
- FedPSO: Federated Learning Using Particle Swarm Optimization to Reduce Communication Costs☆19Updated 2 years ago
- Source code for 'Dual Attention Based FL for Wireless Traffic Prediction'☆70Updated 3 years ago
- Federated Learning for Energy-balanced Client Selection in Mobile Edge Computing☆35Updated last year
- Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation☆36Updated 4 years ago
- ☆11Updated 3 years ago
- Publication catalog for research on Federated RL (FRL).☆84Updated 4 years ago
- [IEEE Access] "Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-constrained Edge Computing Systems" and […☆36Updated 2 years ago
- Code for 'Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing', published in IEEE TPDS.☆93Updated 3 years ago
- FedFormer: Contextual Federation with Attention in Reinforcement Learning (AAMAS 2023)☆43Updated 10 months ago
- We will implement this framework.☆32Updated 3 years ago
- Federated Reinforcement Learning project☆30Updated 2 years ago