Searched for: subject:"Quantum%5C+machine%5C+learning"
(1 - 5 of 5)
document
Phillipson, F. (author), Wezeman, R.S. (author), Chiscop, I. (author)
Communication networks are managed more and more by using artificial intelligence. Anomaly detection, network monitoring and user behaviour are areas where machine learning offers advantages over more traditional methods. However, computer power is increasingly becoming a limiting factor in machine learning tasks. The rise of quantum computers...
article 2021
document
Phillipson, F. (author)
A quantum computer that is useful in practice, is expected to be developed in the next few years. An important application is expected to be machine learning, where benefits are expected on run time, capacity and learning efficiency. In this paper, these benefits are presented and for each benefit an example application is presented. A quantum...
conference paper 2020
document
Phillipson, F. (author), Wezeman, R.S. (author), Chiscop, I. (author)
There is a growing trend in using machine learning techniques for detecting environmental context in communication networks. Machine learning is one of the promising candidate areas where quantum computing can show a quantum advantage over their classical algorithmic counterpart on near term Noisy Intermediate-Scale Quantum (NISQ) devices. The...
conference paper 2020
document
Meinhardt, N. (author), Neumann, N.M.P. (author), Phillipson, F. (author)
conference paper 2020
document
Phillipson, F. (author), Wezeman, R.S (author), Chiscop, I. (author)
There is a growing trend in using machine learning techniques for detecting environmental context in communication networks. Machine learning is one of the promising candidate areas where quantum computing can show a quantum advantage over their classical algorithmic counterpart on near term Noisy Intermediate-Scale Quantum (NISQ) devices. The...
conference paper 2021
Searched for: subject:"Quantum%5C+machine%5C+learning"
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