Neural networks and numerical analysis:
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...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berlin ; Boston
De Gruyter
[2022]
|
| Schriftenreihe: | De Gruyter series in applied and numerical Mmthematics
volume 6 |
| Schlagworte: | |
| Online-Zugang: | DE-1043 DE-1046 DE-858 DE-898 DE-859 DE-860 DE-91 DE-706 DE-739 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | Description based on online resource; title from PDF title page (publisher's Web site, viewed 30. Aug 2022) |
| Beschreibung: | 1 Online-Ressource (XV, 156 Seiten) Diagramme |
| ISBN: | 9783110783186 9783110783261 |
| DOI: | 10.1515/9783110783186 |
Internformat
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| 520 | |a 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 | ||
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Datensatz im Suchindex
| _version_ | 1828111038104469504 |
|---|---|
| adam_text | |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Després, Bruno 1965- |
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| bvnumber | BV048457633 |
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| discipline | Informatik Mathematik |
| discipline_str_mv | Informatik Mathematik |
| doi_str_mv | 10.1515/9783110783186 |
| format | Electronic eBook |
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| id | DE-604.BV048457633 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T20:32:37Z |
| indexdate | 2025-03-31T12:02:24Z |
| institution | BVB |
| isbn | 9783110783186 9783110783261 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033835685 |
| oclc_num | 1344257757 |
| open_access_boolean | |
| owner | DE-1043 DE-1046 DE-858 DE-859 DE-860 DE-739 DE-91 DE-BY-TUM DE-898 DE-BY-UBR DE-706 DE-11 |
| owner_facet | DE-1043 DE-1046 DE-858 DE-859 DE-860 DE-739 DE-91 DE-BY-TUM DE-898 DE-BY-UBR DE-706 DE-11 |
| physical | 1 Online-Ressource (XV, 156 Seiten) Diagramme |
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| publishDate | 2022 |
| publishDateSearch | 2022 |
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| publisher | De Gruyter |
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| series | De Gruyter series in applied and numerical Mmthematics |
| series2 | De Gruyter series in applied and numerical Mmthematics |
| spelling | Després, Bruno 1965- Verfasser (DE-588)1138723223 aut Neural networks and numerical analysis Bruno Després Berlin ; Boston De Gruyter [2022] © 2022 1 Online-Ressource (XV, 156 Seiten) Diagramme txt rdacontent c rdamedia cr rdacarrier De Gruyter series in applied and numerical Mmthematics volume 6 Description based on online resource; title from PDF title page (publisher's Web site, viewed 30. Aug 2022) 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 In English Neuronale Netze Numerische Mathematik Näherungseigenschaften MATHEMATICS / Numerical Analysis bisacsh Erscheint auch als Druck-Ausgabe 978-3-11-078312-4 (DE-604)BV048554181 De Gruyter series in applied and numerical Mmthematics volume 6 (DE-604)BV044780808 6 https://doi.org/10.1515/9783110783186 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Després, Bruno 1965- Neural networks and numerical analysis Neuronale Netze Numerische Mathematik Näherungseigenschaften MATHEMATICS / Numerical Analysis bisacsh De Gruyter series in applied and numerical Mmthematics |
| title | Neural networks and numerical analysis |
| title_auth | Neural networks and numerical analysis |
| title_exact_search | Neural networks and numerical analysis |
| title_exact_search_txtP | 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_short | Neural networks and numerical analysis |
| title_sort | neural networks and numerical analysis |
| topic | Neuronale Netze Numerische Mathematik Näherungseigenschaften MATHEMATICS / Numerical Analysis bisacsh |
| topic_facet | Neuronale Netze Numerische Mathematik Näherungseigenschaften MATHEMATICS / Numerical Analysis |
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