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9783030438821: Recent Trends in Learning From Data

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ISBN 10 : 3030438821 ISBN 13 : 9783030438821

Editeur : Springer, 2020

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Introduction: Recent Trends in Learning From Data.- Learned data structures.- Deep Randomized Neural Networks.- Tensor Decompositions and Practical Applications.- Deep learning for graphs.- Limitations of Shallow Networks.- Fairness in Machine Learning.- Online Continual Learning on Sequences.

Les informations fournies dans la section � Synopsis � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteurSpringer
Date d'�dition2020
ISBN 10 3030438821
ISBN 13 9783030438821
ReliureReli�
Langueanglais
Nombre de pages232
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9783030438852: Recent Trends in Learning From Data: Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL2019)

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ISBN 10 : 3030438856 ISBN 13 : 9783030438852
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Recent Trends in Learning From Data

Oneto, Luca|Navarin, Nicol�|Sperduti, Alessandro|Anguita, Davide

Edit� par Springer International Publishing, 2020

ISBN 10 : 3030438821 ISBN 13 : 9783030438821

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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Gathers tutorials from the 2019 INNS Big Data and Deep Learning ConferenceDescribes cutting-edge AI-based tools and applicationsOffers essential guidance on the design and analysis of advanced AI-. N� de r�f. du vendeur 448682176

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Recent Trends in Learning From Data : Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL2019)

Luca Oneto

Edit� par Springer International Publishing, 2020

ISBN 10 : 3030438821 ISBN 13 : 9783030438821

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research. N� de r�f. du vendeur 9783030438821

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Recent Trends in Learning From Data

Luca Oneto

Edit� par Springer International Publishing Apr 2020, 2020

ISBN 10 : 3030438821 ISBN 13 : 9783030438821

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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research. 232 pp. Englisch. N� de r�f. du vendeur 9783030438821

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Recent Trends in Learning From Data (Studies in Computational Intelligence, 896)

Oneto

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ISBN 10 : 3030438821 ISBN 13 : 9783030438821

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Etat : New. In. N� de r�f. du vendeur ria9783030438821_new

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Recent Trends in Learning From Data

Luca Oneto

Edit� par Springer International Publishing, Springer International Publishing Apr 2020, 2020

ISBN 10 : 3030438821 ISBN 13 : 9783030438821

Neuf Couverture rigide

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Buch. Etat : Neu. Neuware -This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 232 pp. Englisch. N� de r�f. du vendeur 9783030438821

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