Quantum machine learning
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...
| Other Authors: | , , , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin Boston
De Gruyter
[2020]
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| Series: | De Gruyter frontiers in computational intelligence ;
v. 6. |
| Subjects: | |
| Online Access: | EBSCOhost Перейти в каталог НБ ТГУ |
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| 020 | |a 9783110670721 | ||
| 020 | |a 3110670720 | ||
| 020 | |z 9783110670646 | ||
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| 082 | 0 | 4 | |a 006.3/1 |2 23 |
| 049 | |a MAIN | ||
| 245 | 0 | 0 | |a Quantum machine learning |c edited by Siddhartha Bhattacharyya, Indrajit Pan, Ashish Mani, Sourav De, Elizabeth Behrman, Susanta Chakraborti |
| 264 | 1 | |a Berlin |a Boston |b De Gruyter |c [2020] | |
| 300 | |a 1 online resource | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a De Gruyter Frontiers in Computational Intelligence |v volume 6 | |
| 588 | |a Description based on online resource; title from PDF title page (viewed on September 10, 2020) | ||
| 504 | |a Includes bibliographical references and index | ||
| 505 | 0 | 0 | |t Frontmatter -- |t Contents -- |t List of Contributors -- |t Preface -- |t 1. Introduction to quantum machine learning -- |t 2. Topographic representation for quantum machine learning -- |t 3. Quantum optimization for machine learning -- |t 4. From classical to quantum machine learning -- |t 5. Quantum inspired automatic clustering algorithms: A comparative study of Genetic algorithm and Bat algorithm -- |t 6. Conclusion -- |t Index |
| 520 | |a 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 | ||
| 653 | 0 | |a Machine learning. | |
| 653 | 0 | |a Quantum theory. | |
| 653 | 4 | |a Algorithmus | |
| 653 | 4 | |a Künstliche Intelligenz | |
| 653 | 4 | |a Maschinelles Lernen | |
| 653 | 4 | |a Quantum Computing | |
| 653 | 7 | |a COMPUTERS / Intelligence (AI) & Semantics |2 bisacsh | |
| 655 | 0 | |a EBSCO eBooks |9 905790 | |
| 655 | 4 | |a Electronic books |9 899821 | |
| 700 | 1 | |a Bhattacharyya, Siddhartha, |d 1975- |9 913417 | |
| 700 | 1 | |a Pan, Indrajit, |d 1983- |9 913624 | |
| 700 | 1 | |a Mani, Ashish |4 edt |9 913625 | |
| 700 | 1 | |a De, Sourav |d 1979- |9 913626 | |
| 700 | 1 | |a Behrman, Elizabeth |4 edt |9 913627 | |
| 700 | 1 | |a Chakraborti, Susanta |4 edt |9 913628 | |
| 830 | 0 | |a De Gruyter frontiers in computational intelligence ; |v v. 6. |9 911816 | |
| 856 | 4 | 0 | |3 EBSCOhost |u https://www.lib.tsu.ru/limit/2023/EBSCO/2499096.pdf |
| 856 | |y Перейти в каталог НБ ТГУ |u https://koha.lib.tsu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=1014394 | ||
| 910 | |a EBSCO eBooks | ||
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| 999 | |c 1014394 |d 1014394 | ||