Neural Networks and Numerical Analysis / / Bruno Després.
This book uses numerical analysis as the main tool to investigate methods in machine learning and neural networks. The efficiency of neural network representations for general functions and for polynomial functions is studied in detail, together with an original description of the Latin hypercube me...
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| Place / Publishing House: | Berlin ;, Boston : : De Gruyter, , [2022] ©2022 |
| Year of Publication: | 2022 |
| Language: | English |
| Series: | De Gruyter Series in Applied and Numerical Mathematics ,
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| Physical Description: | 1 online resource (XVI, 158 p.) |
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Després, Bruno, author. aut http://id.loc.gov/vocabulary/relators/aut Neural Networks and Numerical Analysis / Bruno Després. Berlin ; Boston : De Gruyter, [2022] ©2022 1 online resource (XVI, 158 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda De Gruyter Series in Applied and Numerical Mathematics , 2512-1820 ; 6 Frontmatter -- Introduction -- Acknowledgement -- Contents -- 1 Objective functions, neural networks, and linear algebra -- 2 Approximation properties -- 3 A functional equation -- 4 Datasets -- 5 Stochastic gradient methods -- 6 Examples and research in the field -- Bibliography -- Index restricted access http://purl.org/coar/access_right/c_16ec online access with authorization star This book uses numerical analysis as the main tool to investigate methods in machine learning and neural networks. The efficiency of neural network representations for general functions and for polynomial functions is studied in detail, together with an original description of the Latin hypercube method and of the ADAM algorithm for training. Furthermore, unique features include the use of Tensorflow for implementation session, and the description of on going research about the construction of new optimized numerical schemes. Issued also in print. Mode of access: Internet via World Wide Web. In English. Description based on online resource; title from PDF title page (publisher's Web site, viewed 29. Mai 2023) Neuronale Netze. Numerische Mathematik. Näherungseigenschaften. MATHEMATICS / Numerical Analysis. bisacsh neural networks, machine learning, artificial initelligence, Tensorflow, numerical schemes, partial differential equations. Title is part of eBook package: De Gruyter DG Plus DeG Package 2022 Part 1 9783110766820 Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE 2022 English 9783110993899 Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE 2022 9783110994810 ZDB-23-DGG Title is part of eBook package: De Gruyter EBOOK PACKAGE Mathematics 2022 English 9783110993868 Title is part of eBook package: De Gruyter EBOOK PACKAGE Mathematics 2022 9783110770445 ZDB-23-DMA EPUB 9783110783261 print 9783110783124 https://doi.org/10.1515/9783110783186 https://www.degruyter.com/isbn/9783110783186 Cover https://www.degruyter.com/document/cover/isbn/9783110783186/original |
| language |
English |
| format |
eBook |
| author |
Després, Bruno, Després, Bruno, |
| spellingShingle |
Després, Bruno, Després, Bruno, Neural Networks and Numerical Analysis / De Gruyter Series in Applied and Numerical Mathematics , Frontmatter -- Introduction -- Acknowledgement -- Contents -- 1 Objective functions, neural networks, and linear algebra -- 2 Approximation properties -- 3 A functional equation -- 4 Datasets -- 5 Stochastic gradient methods -- 6 Examples and research in the field -- Bibliography -- Index |
| author_facet |
Després, Bruno, Després, Bruno, |
| author_variant |
b d bd b d bd |
| author_role |
VerfasserIn VerfasserIn |
| author_sort |
Després, Bruno, |
| title |
Neural Networks and Numerical Analysis / |
| title_full |
Neural Networks and Numerical Analysis / Bruno Després. |
| title_fullStr |
Neural Networks and Numerical Analysis / Bruno Després. |
| title_full_unstemmed |
Neural Networks and Numerical Analysis / Bruno Després. |
| title_auth |
Neural Networks and Numerical Analysis / |
| title_alt |
Frontmatter -- Introduction -- Acknowledgement -- Contents -- 1 Objective functions, neural networks, and linear algebra -- 2 Approximation properties -- 3 A functional equation -- 4 Datasets -- 5 Stochastic gradient methods -- 6 Examples and research in the field -- Bibliography -- Index |
| title_new |
Neural Networks and Numerical Analysis / |
| title_sort |
neural networks and numerical analysis / |
| series |
De Gruyter Series in Applied and Numerical Mathematics , |
| series2 |
De Gruyter Series in Applied and Numerical Mathematics , |
| publisher |
De Gruyter, |
| publishDate |
2022 |
| physical |
1 online resource (XVI, 158 p.) Issued also in print. |
| contents |
Frontmatter -- Introduction -- Acknowledgement -- Contents -- 1 Objective functions, neural networks, and linear algebra -- 2 Approximation properties -- 3 A functional equation -- 4 Datasets -- 5 Stochastic gradient methods -- 6 Examples and research in the field -- Bibliography -- Index |
| isbn |
9783110783186 9783110766820 9783110993899 9783110994810 9783110993868 9783110770445 9783110783261 9783110783124 |
| issn |
2512-1820 ; |
| url |
https://doi.org/10.1515/9783110783186 https://www.degruyter.com/isbn/9783110783186 https://www.degruyter.com/document/cover/isbn/9783110783186/original |
| illustrated |
Not Illustrated |
| doi_str_mv |
10.1515/9783110783186 |
| oclc_num |
1336990265 |
| work_keys_str_mv |
AT despresbruno neuralnetworksandnumericalanalysis |
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n |
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(DE-B1597)617483 (OCoLC)1336990265 |
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cr |
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Title is part of eBook package: De Gruyter DG Plus DeG Package 2022 Part 1 Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE 2022 English Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE 2022 Title is part of eBook package: De Gruyter EBOOK PACKAGE Mathematics 2022 English Title is part of eBook package: De Gruyter EBOOK PACKAGE Mathematics 2022 |
| is_hierarchy_title |
Neural Networks and Numerical Analysis / |
| container_title |
Title is part of eBook package: De Gruyter DG Plus DeG Package 2022 Part 1 |
| _version_ |
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