Quantum Machine Learning / / ed. by Siddhartha Bhattacharyya, Indrajit Pan, Ashish Mani, Elizabeth Behrman, Susanta Chakraborti, Sourav De.
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 inf...
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Superior document: | Title is part of eBook package: De Gruyter DG Ebook Package English 2020 |
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HerausgeberIn: | |
MitwirkendeR: | |
Place / Publishing House: | Berlin ;, Boston : : De Gruyter, , [2020] ©2020 |
Year of Publication: | 2020 |
Language: | English |
Series: | De Gruyter Frontiers in Computational Intelligence ,
6 |
Online Access: | |
Physical Description: | 1 online resource (XIII, 118 p.) |
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Other title: | Frontmatter -- Contents -- List of Contributors -- Preface -- 1. Introduction to quantum machine learning -- 2. Topographic representation for quantum machine learning -- 3. Quantum optimization for machine learning -- 4. From classical to quantum machine learning -- 5. Quantum inspired automatic clustering algorithms: A comparative study of Genetic algorithm and Bat algorithm -- 6. Conclusion -- Index |
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Summary: | 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. |
Format: | Mode of access: Internet via World Wide Web. |
ISBN: | 9783110670707 9783110696288 9783110696271 9783110659061 9783110704716 9783110704518 9783110704815 9783110704617 |
ISSN: | 2512-8868 ; |
DOI: | 10.1515/9783110670707 |
Access: | restricted access |
Hierarchical level: | Monograph |
Statement of Responsibility: | ed. by Siddhartha Bhattacharyya, Indrajit Pan, Ashish Mani, Elizabeth Behrman, Susanta Chakraborti, Sourav De. |