Quantum machine learning[electronic resource]

  • 其他作者: Bhattacharyya, Siddhartha,
  • 出版: Berlin ;Boston : De Gruyter c2020.
  • 版本: 1st ed.
  • 稽核項: 1 online resource (xiii, 118 p.) :ill.
  • 叢書名: De Gruyter frontiers in computational intelligence,6
  • 標題: Machine learning. , Quantum theory.
  • ISBN: 3110670720 , 9783110670721
  • ISBN: 9783110670646 , 311067064X , 2512-8868 ;
  • 試查全文@TNUA:
  • 附註: Includes bibliographical references and index.
  • 摘要: 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.
  • 電子資源: https://dbs.tnua.edu.tw/login?url=https://www.degruyter.com/isbn/9783110670707
  • 系統號: 005338610
  • 資料類型: 電子書
  • 讀者標籤: 需登入
  • 引用網址: 複製連結