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- W3134736897 abstract "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 goal of this paper is to give a practical overview of (supervised) quantum machine learning techniques to be used for indoor-outdoor detection. Due to the small number of qubits in current quantum hardware, real application is not yet feasible. Our work is intended to be a starting point for further explorations of quantum machine learning techniques for indoor-outdoor detection." @default.
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- W3134736897 date "2021-01-01" @default.
- W3134736897 modified "2023-09-26" @default.
- W3134736897 title "Three Quantum Machine Learning Approaches for Mobile User Indoor-Outdoor Detection" @default.
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- W3134736897 doi "https://doi.org/10.1007/978-3-030-70866-5_11" @default.
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