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Añadir al carritoHardcover. Condición: Used-Very Good. Cloth, dj. Minor shelf wear.
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Añadir al carritoCondición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Dust jacket in good condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1000grams, ISBN:9780262072977.
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Añadir al carritoCondición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Añadir al carritoCondición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Idioma: Inglés
Publicado por The MIT Press Bookstore, 2008
ISBN 10: 0262072971 ISBN 13: 9780262072977
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Añadir al carritoCondición: Used. pp. xii + 316.
Idioma: Inglés
Publicado por The MIT Press Bookstore, 2008
ISBN 10: 0262072971 ISBN 13: 9780262072977
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Añadir al carritoCondición: Used. pp. xii + 316 55 Illus.
Idioma: Inglés
Publicado por The MIT Press Bookstore, 2008
ISBN 10: 0262072971 ISBN 13: 9780262072977
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoCondición: Used. pp. xii + 316.
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Añadir al carritoTaschenbuch. Condición: Neu. On small sample experiments in neuro-imaging | Cyril Goutte (u. a.) | Taschenbuch | 28 S. | Englisch | 2017 | GRIN Verlag | EAN 9783668438828 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu.
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Publicado por Springer-Nature New York Inc, 2020
ISBN 10: 3030473570 ISBN 13: 9783030473570
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 588 pages. 9.25x6.10x1.61 inches. In Stock.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Doctoral Thesis / Dissertation from the year 1997 in the subject Computer Sciences - Artificial Intelligence, grade: n/a, , language: English, abstract: This thesis deals with the problem of statistical learning. By 'learning'', we mean a process by which we obtain a model of a phenomenon using data measured on it. We focus on system identification and time series modelling, and our work is naturally slightly influenced by this concern. We will for example evoke only regression estimation, and no classification problem. However, most theoretical and practical aspects presented herein can easily be adapted. We study neural networks models. This research has traditionally been linked to computer science and artificial intelligence. In the last few years however, two distinct lines of thoughts seem to diverge: the first one stays close to the biological origins of the term - we will call it 'neuro-biological'; the second considers neural networks as a model, and studies them from a statistical point of view. Our work concerns the second of these lines. Furthermore, we try to stay independent of any specific application, and keep a general approach to neural networks. We attempt to exhibit the links between neural networks and statistics, and show that neural computation can be naturally placed in the realm of traditional statistics. We thus compare neural networks to other models: linear regression as well as non-parametric estimators. We also consider some of the numerous learning techniques developed for neural models, and try to compare them, from both a theoretical and applied point of view.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030473570 ISBN 13: 9783030473570
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 53,49
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020, which was planned to take place in Ottawa, ON, Canada. Due to the COVID-19 pandemic, however, it was held virtually duringMay 13-15, 2020.The 31 regular papers and 24 short papers presented together with 4 Graduate Student Symposium papers were carefully reviewed and selected from a total of 175 submissions.The selected papers cover a wide range of topics, including machine learning, pattern recognition, natural language processing, knowledge representation, cognitive aspects of AI, ethics of AI, and other important aspects of AI research.
Librería: preigu, Osnabrück, Alemania
EUR 50,35
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Añadir al carritoTaschenbuch. Condición: Neu. Advances in Artificial Intelligence | 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020, Ottawa, ON, Canada, May 13-15, 2020, Proceedings | Cyril Goutte (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xv | Englisch | 2020 | Springer | EAN 9783030473570 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Añadir al carritoTaschenbuch. Condición: Neu. Statistical learning and regularisation for regression | Application to system identification and time series modelling | Cyril Goutte | Taschenbuch | 164 S. | Englisch | 2017 | GRIN Verlag | EAN 9783668443204 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu.
Librería: Mispah books, Redhill, SURRE, Reino Unido
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Añadir al carritoPaperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Añadir al carritoCouverture souple. Condición: Neuf.
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Doctoral Thesis / Dissertation from the year 1997 in the subject Computer Sciences - Artificial Intelligence, grade: n/a, , language: English, abstract: This thesis deals with the problem of statistical learning. By 'learning'', we mean a process by which we obtain a model of a phenomenon using data measured on it. We focus on system identification and time series modelling, and our work is naturally slightly influenced by this concern. We will for example evoke only regression estimation, and no classification problem. However, most theoretical and practical aspects presented herein can easily be adapted. We study neural networks models. This research has traditionally been linked to computer science and artificial intelligence. In the last few years however, two distinct lines of thoughts seem to diverge: the first one stays close to the biological origins of the term - we will call it 'neuro-biological'; the second considers neural networks as a model, and studies them from a statistical point of view. Our work concerns the second of these lines. Furthermore, we try to stay independent of any specific application, and keep a general approach to neural networks. We attempt to exhibit the links between neural networks and statistics, and show that neural computation can be naturally placed in the realm of traditional statistics. We thus compare neural networks to other models: linear regression as well as non-parametric estimators. We also consider some of the numerous learning techniques developed for neural models, and try to compare them, from both a theoretical and applied point of view. 164 pp. Englisch.
Idioma: Inglés
Publicado por Springer International Publishing Mai 2020, 2020
ISBN 10: 3030473570 ISBN 13: 9783030473570
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 53,49
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020, which was planned to take place in Ottawa, ON, Canada. Due to the COVID-19 pandemic, however, it was held virtually duringMay 13-15, 2020.The 31 regular papers and 24 short papers presented together with 4 Graduate Student Symposium papers were carefully reviewed and selected from a total of 175 submissions.The selected papers cover a wide range of topics, including machine learning, pattern recognition, natural language processing, knowledge representation, cognitive aspects of AI, ethics of AI, and other important aspects of AI research. 588 pp. Englisch.