| Description |
1 online resource (vii, 221 pages) : illustrations (some color) |
| Series |
Studies in computational intelligence, 1860-949X ; volume 896 |
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Studies in computational intelligence ; v. 896. 1860-949X
|
| Contents |
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 |
| Summary |
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 |
| Notes |
Online resource; title from PDF title page (SpringerLink, viewed April 15, 2020) |
| Subject |
Big data -- Congresses
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Machine learning -- Congresses
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Machine learning.
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Databases.
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Artificial intelligence.
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Computers -- Intelligence (AI) & Semantics.
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Computers -- Data Processing.
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Technology & Engineering -- Engineering (General)
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Big data
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Machine learning
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| Genre/Form |
proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
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| Author |
Oneto, Luca, editor
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Navarin, Nicolò, editor
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Sperduti, A. (Alessandro), editor.
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Anguita, Davide, editor
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| ISBN |
9783030438838 |
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303043883X |
|
