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    Quantum machine learning

    Date
    2020-06-08
    Author
    Bhattacharyya, Siddhartha
    Pan, Indrajit
    Mani, Ashish
    De, Sourav
    Behrman, Elizabeth C.
    Chakrabarti, Susanta
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    Citation
    Bhattacharyya, S., Pan, I., Mani, A., De, S., Behrman, E., & Chakraborti, S. (Eds.). (2020). Quantum Machine Learning. Berlin, Boston: De Gruyter
    Abstract
    Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system. While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices. New trends in Machine Learning based on Quantum Computing and Quantum Algorithms Examples on real life applications Illustrative diagrams and coding examples.
    Description
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    URI
    https://doi.org/10.1515/9783110670707
    https://soar.wichita.edu/handle/10057/19541
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    • PHY Research Publications (till 2011)

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