Applications of distributed machine learning for the Internet-of-Things: A comprehensive survey
The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
Applications of Distributed Machine Learning for the Internet-of-Things: A Comprehensive Survey
The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
In-network computation for large-scale federated learning over wireless edge networks
Most conventional Federated Learning (FL) models are using a star network topology where
all users aggregate their local models at a single server (eg, a cloud server). That causes …
all users aggregate their local models at a single server (eg, a cloud server). That causes …
A discrete-time multi-hop consensus protocol for decentralized federated learning
This paper presents a Federated Learning (FL) algorithm that allows the decentralization of
all FL solutions that employ a model-averaging procedure. The proposed algorithm proves …
all FL solutions that employ a model-averaging procedure. The proposed algorithm proves …
Privacy-Preserving AI Framework for 6G-Enabled Consumer Electronics
In the realm of consumer electronics for 6G communication, AI has emerged as a significant
player. However, the proliferation of devices at the edge of network causes the generation of …
player. However, the proliferation of devices at the edge of network causes the generation of …
A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and …
A Majeed, SO Hwang - IEEE Access, 2024 - ieeexplore.ieee.org
Federated learning (FL) is considered a de facto standard for privacy preservation in AI
environments because it does not require data to be aggregated in some central place to …
environments because it does not require data to be aggregated in some central place to …
Resilient, Secure and Private Coded Distributed Convolution Computing for Mobile-Assisted Metaverse
The Metaverse is recognized as the next-generation Internet that provides immersive
interaction experiences for users. Convolutional neural networks (CNNs) play a crucial role …
interaction experiences for users. Convolutional neural networks (CNNs) play a crucial role …
pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving
Deep learning-based Autonomous Driving (AD) models often exhibit poor generalization
due to data heterogeneity in an ever domain-shifting environment. While Federated …
due to data heterogeneity in an ever domain-shifting environment. While Federated …
Securing Blockchain Systems: A Novel Collaborative Learning Framework to Detect Attacks in Transactions and Smart Contracts
With the escalating prevalence of malicious activities exploiting vulnerabilities in blockchain
systems, there is an urgent requirement for robust attack detection mechanisms. To address …
systems, there is an urgent requirement for robust attack detection mechanisms. To address …
Federated Learning for Cyberattack Detection in Decentralized Networks
VK Tran - 2024 - opus.lib.uts.edu.au
Recently, the rapid development of various technologies, such as blockchain and Internet-of-
Things (IoT), has enabled numerous applications to become integral to many aspects of our …
Things (IoT), has enabled numerous applications to become integral to many aspects of our …