Machine learning for intelligent authentication in 5G and beyond wireless networks
… Machine learning paradigms for intelligent authentication design are presented, namely
for … /unsupervised/reinforcement learning algorithms. In a nutshell, the machine-learning-based …
for … /unsupervised/reinforcement learning algorithms. In a nutshell, the machine-learning-based …
Recent advances in data-driven wireless communication using gaussian processes: a comprehensive survey
… with traditional paradigms in wireless communication, a … machine learning for data-driven
wireless communications, in this … in wireless communications due to their interpretable learning …
wireless communications, in this … in wireless communications due to their interpretable learning …
Will mobile learning bring a paradigm shift in higher education?
L Rajasingham - Education Research International, 2011 - Wiley Online Library
… In assessing the potential of m-learning as a subset of e-learning to effect a new paradigm
of higher education, this paper seeks a mobile-learning approach that retains the original …
of higher education, this paper seeks a mobile-learning approach that retains the original …
[图书][B] White Paper on Machine Learning in 6G Wireless Communication Networks: 6G Research Visions, No. 7, 2020
… wireless domain. In this paper, we offer a vision of how ML will impact wireless communications
… the highest potential to be used in wireless networks. We then discuss the problems that …
… the highest potential to be used in wireless networks. We then discuss the problems that …
Mobile learning new trends in emerging computing paradigms: An analytical approach seeking performance efficiency
K Mohiuddin, MN Miladi, M Ali Khan… - … Communications …, 2022 - Wiley Online Library
… learning objects [16]. In this context, the current study presents these paradigms’ features that
facilitate m-learning … opportunities of such paradigms that optimize the m-learning system’s …
facilitate m-learning … opportunities of such paradigms that optimize the m-learning system’s …
Transfer learning promotes 6G wireless communications: Recent advances and future challenges
M Wang, Y Lin, Q Tian, G Si - IEEE Transactions on Reliability, 2021 - ieeexplore.ieee.org
… algorithms used in different wireless communication fields, such as … wireless localization
and intrusion detection in wireless … , “Machine learning paradigms for next-generation wireless …
and intrusion detection in wireless … , “Machine learning paradigms for next-generation wireless …
Deep reinforcement learning based resource allocation approach for wireless networks considering network slicing paradigm
… the model for the considered wireless communication system; section IV … learning; section
VI describes the main concepts of network slicing and its main advantages for modern wireless …
VI describes the main concepts of network slicing and its main advantages for modern wireless …
[PDF][PDF] Cognitive radio network—A new paradigm in wireless communication
… radio is an intelligent wireless communication system that is aware of its surrounding
environment and uses the methodology of understanding-by-building to learn from the environment …
environment and uses the methodology of understanding-by-building to learn from the environment …
Deep-learning-based wireless resource allocation with application to vehicular networks
… in wireless communications developed over the past few decades to complement the
datadriven deep-learning … 1) Supervised Learning Paradigm: The DNNs are applied to learn the …
datadriven deep-learning … 1) Supervised Learning Paradigm: The DNNs are applied to learn the …
Quantum machine learning for 6G communication networks: State-of-the-art and vision for the future
… Today’s wireless communication networks are expected to experience a fundamental
paradigm shift towards smart and intelligent radio environments [17]. The main question around …
paradigm shift towards smart and intelligent radio environments [17]. The main question around …