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- W3204567548 abstract "The paper demonstrates how to realize neural vector quantizers by means of quantum computing approaches. Particularly, we consider self-organizing maps and the neural gas vector quantizer for unsupervised learning as well as generalized learning vector quantization for classification learning. We show how quantum computing concepts can be adopted for these algorithms. The respective mathematical framework is explained in detail." @default.
- W3204567548 created "2021-10-11" @default.
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- W3204567548 date "2021-01-01" @default.
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- W3204567548 title "Quantum-Hybrid Neural Vector Quantization – A Mathematical Approach" @default.
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- W3204567548 doi "https://doi.org/10.1007/978-3-030-87986-0_22" @default.
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