Quantum machine learning (QML) is an emerging research area that combines quantum computing with machine learning to exploit quantum superposition, entanglement, interference, and high-dimensional Hilbert-space representations. This paper presents a concise survey of QML models and algorithms for near-term noisy interm...
Ton That Tam Dinh, Manh Cuong Ho, Ayalneh Bitew Wondmagegn et al.· International Conference on...· 0 citations
Unmanned aerial vehicles (UAVs) are emerging as mobile edge nodes for temporary coverage, aerial sensing, disaster response, public-safety monitoring, intelligent transportation, and smart-agriculture services. Although federated learning (FL) enables distributed model training without transferring raw data, convention...
Ton That Tam Dinh, Manh Cuong Ho, Ayalneh Bitew Wondmagegn et al.· International Conference on...· 0 citations
Open Radio Access Network (O-RAN) enables flexible and intelligent radio access network operation through disaggregation, virtualization, open interfaces, and RAN Intelligent Controllers (RICs). At the same time, the data required to train artificial intelligence and machine learning models in O-RAN is naturally distri...
Junsuk Oh, Donghyun Lee, Chunghyun Lee et al.· International Conference on...· 0 citations
Intent-Based Networking (IBN) has emerged as a promising paradigm for simplifying network management by allowing operators and applications to specify high-level service objectives rather than low-level device configurations. Early IBN research was mainly developed in Software-Defined Networking (SDN), Network Function...
Dongwook Won, Thanh Thien-An Dang, Ton That Tam Dinh et al.· International Conference on...· 0 citations
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