Quantum Machine Learning
著者
書誌事項
Quantum Machine Learning
（De Gruyter frontiers in computational intelligence, v. 6）
De Gruyter, c2020
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注記
Other editors: Indrajit Pan, Ashish Mani, Sourav De, Elizabeth Behrman, Susanta Chakraborti
Includes bibliographical references and index
内容説明・目次
内容説明
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.
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