Federated learning for internet of things: A comprehensive survey
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …
A survey on federated learning for resource-constrained IoT devices
Federated learning (FL) is a distributed machine learning strategy that generates a global
model by learning from multiple decentralized edge clients. FL enables on-device training …
model by learning from multiple decentralized edge clients. FL enables on-device training …
Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …
increasingly appealing to exploit distributed data communication and learning. Specifically …
[HTML][HTML] Asynchronous federated learning on heterogeneous devices: A survey
Federated learning (FL) is a kind of distributed machine learning framework, where the
global model is generated on the centralized aggregation server based on the parameters of …
global model is generated on the centralized aggregation server based on the parameters of …
Personalized federated learning framework for network traffic anomaly detection
J Pei, K Zhong, MA Jan, J Li - Computer Networks, 2022 - Elsevier
With the widespread use of real-time sensors in various fields, such as IoT systems, it is
important to improve the performance of most network traffic anomaly detection methods …
important to improve the performance of most network traffic anomaly detection methods …
Electricity consumer characteristics identification: A federated learning approach
Nowadays, smart meters are deployed in millions of residential households to gain
significant insights from fine-grained electricity consumption data. The information extracted …
significant insights from fine-grained electricity consumption data. The information extracted …
A survey on heterogeneous federated learning
Federated learning (FL) has been proposed to protect data privacy and virtually assemble
the isolated data silos by cooperatively training models among organizations without …
the isolated data silos by cooperatively training models among organizations without …
Federated learning for computationally constrained heterogeneous devices: A survey
With an increasing number of smart devices like internet of things devices deployed in the
field, offloading training of neural networks (NNs) to a central server becomes more and …
field, offloading training of neural networks (NNs) to a central server becomes more and …
Towards efficient communications in federated learning: A contemporary survey
In the traditional distributed machine learning scenario, the user's private data is transmitted
between clients and a central server, which results in significant potential privacy risks. In …
between clients and a central server, which results in significant potential privacy risks. In …
Federated deep learning for heterogeneous edge computing
Nowadays, there is an ever-increasing deployment of intelligent edge devices, such as
smartphones, wearable devices, and autonomous vehicles. It is enabled by the integration …
smartphones, wearable devices, and autonomous vehicles. It is enabled by the integration …