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Kok-Lim Alvin Yau
Researcher at Sunway University
Publications - 119
Citations - 3252
Kok-Lim Alvin Yau is an academic researcher from Sunway University. The author has contributed to research in topics: Cognitive radio & Reinforcement learning. The author has an hindex of 25, co-authored 106 publications receiving 1942 citations. Previous affiliations of Kok-Lim Alvin Yau include University of Kuala Lumpur & Victoria University of Wellington.
Papers
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Edge Computing in 5G: A Review
TL;DR: A taxonomy of edge computing in 5G is established, which gives an overview of existing state-of-the-art solutions of edge Computing in5G on the basis of objectives, computational platforms, attributes, 5G functions, performance measures, and roles.
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5G-Based Smart Healthcare Network: Architecture, Taxonomy, Challenges and Future Research Directions
TL;DR: A state-of-the-art review of the 5G and IoT enabled smart healthcare, Taxonomy, research trends, challenges, and future research directions is provided.
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Federated Learning for Vehicular Internet of Things: Recent Advances and Open Issues
TL;DR: The significance and technical challenges of applying FL in vehicular IoT, and future research directions are discussed, and a brief survey of existing studies on FL and its use in wireless IoT is conducted.
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Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges
Muhammad Usama,Junaid Qadir,Aunn Raza,Hunain Arif,Kok-Lim Alvin Yau,Yehia Elkhatib,Amir Hussain,Ala Al-Fuqaha +7 more
TL;DR: In this article, the authors provide an overview of unsupervised learning in the domain of networking, and provide a comprehensive review of the current state of the art in this area, by synthesizing insights from previous survey papers.
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A Survey on Reinforcement Learning Models and Algorithms for Traffic Signal Control
TL;DR: Various RL models and algorithms applied to traffic signal control are reviewed in the aspects of the representations of the RL model (i.e., state, action, and reward), performance measures, and complexity to establish a foundation for further investigation in this research field.