An efficient federated distillation learning system for multitask time series classification
This article proposes an efficient federated distillation learning system (EFDLS) for multitask
time series classification (TSC). EFDLS consists of a central server and multiple mobile …
time series classification (TSC). EFDLS consists of a central server and multiple mobile …
[PDF][PDF] Survey of knowledge distillation in federated edge learning
The increasing demand for intelligent services and privacy protection of mobile and Internet
of Things (IoT) devices motivates the wide application of Federated Edge Learning (FEL), in …
of Things (IoT) devices motivates the wide application of Federated Edge Learning (FEL), in …
An intelligent blockchain-assisted cooperative framework for industry 4.0 service management
The shift towards Industry 4.0 has seen significant steps forward with the advancements in
processing, communication, and storage capabilities of Internet of Things (IoT) devices …
processing, communication, and storage capabilities of Internet of Things (IoT) devices …
A federated learning approach with imperfect labels in lora-based transportation systems
Intelligent Transportation System (ITS) helps to improve vehicle health, driver safety, and
passenger comfort. Remotely sharing the information of ITS to train the machine and deep …
passenger comfort. Remotely sharing the information of ITS to train the machine and deep …
A federated learning-based patient monitoring system in internet of medical things
Patient activities' monitoring is a promising application of the Internet of Medical Things
(IoMT), revolutionizing clinical diagnosis. An IoMT uses sensory data collected from smart …
(IoMT), revolutionizing clinical diagnosis. An IoMT uses sensory data collected from smart …
Utilizing transfer learning and pre-trained models for effective forest fire detection: A case study of uttarakhand
HP Gupta, R Mishra - arxiv preprint arxiv:2410.06743, 2024 - arxiv.org
Forest fires pose a significant threat to the environment, human life, and property. Early
detection and response are crucial to mitigating the impact of these disasters. However …
detection and response are crucial to mitigating the impact of these disasters. However …
A personalized federated cloud-edge collaboration framework via cross-client knowledge distillation
As an emerging distributed machine learning paradigm, federated learning has been
extensively used in the domain of cloud–edge computing to collaboratively train models …
extensively used in the domain of cloud–edge computing to collaboratively train models …
Federated Distillation: A Survey
Federated Learning (FL) seeks to train a model collaboratively without sharing private
training data from individual clients. Despite its promise, FL encounters challenges such as …
training data from individual clients. Despite its promise, FL encounters challenges such as …
Students' Decisions in the Context of Social Network Learning Interaction.
Q Li - International Journal of Emerging Technologies in …, 2023 - search.ebscohost.com
In the context of globalization and technology-driven advancements in the 21st century,
learning methods have undergone significant changes. The development of informatization …
learning methods have undergone significant changes. The development of informatization …
Knowledge Distillation in Federated Edge Learning: A Survey
The increasing demand for intelligent services coupled with privacy protection of mobile and
Internet of Things (IoT) devices motivates the widespread adoption of Federated Edge …
Internet of Things (IoT) devices motivates the widespread adoption of Federated Edge …