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Modeling and Optimization in Science and Technologies

Model Selection and Error Estimation in a Nutshell

Authors: Oneto, Luca

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  • Reviews the main approaches to problems of model selection and error estimation
  • Simplifies most of the technical aspects focusing on the applicability of the approaches
  • Presents the intuitions behind the methods, the formalism, and practical algorithms
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eBook 96,29 €
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  • ISBN 978-3-030-24359-3
  • Digitally watermarked, DRM-free
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  • Immediate eBook download after purchase
Hardcover 124,79 €
price for Spain (gross)
  • ISBN 978-3-030-24358-6
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  • Immediate ebook access, if available*, with your print order
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Softcover 88,39 €
price for Spain (gross)
  • Due: August 8, 2020
  • ISBN 978-3-030-24361-6
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

How can we select the best performing data-driven model? How can we rigorously estimate its generalization error? Statistical learning theory answers these questions by deriving non-asymptotic bounds on the generalization error of a model or, in other words, by upper bounding the true error of the learned model based just on quantities computed on the available data. However, for a long time, Statistical learning theory has been considered only an abstract theoretical framework, useful for inspiring new learning approaches, but with limited applicability to practical problems. The purpose of this book is to give an intelligible overview of the problems of model selection and error estimation, by focusing on the ideas behind the different statistical learning theory approaches and simplifying most of the technical aspects with the purpose of making them more accessible and usable in practice. The book starts by presenting the seminal works of the 80’s and includes the most recent results. It discusses open problems and outlines future directions for research.

About the authors

Luca Oneto was born in Rapallo, Italy in 1986. He received his BSc and MSc in Electronic Engineering at the University of Genoa, Italy respectively in 2008 and 2010. In 2014 he received his PhD from the same university in the School of Sciences and Technologies for Knowledge and Information Retrieval with the thesis ``Learning Based On Empirical Data''. In 2017 he obtained the Italian National Scientific Qualification for the role of Associate Professor in Computer Engineering and in 2018 he obtained the one in Computer Science. He worked as Assistant Professor in Computer Engineering at University of Genoa from 2016 to 2019. In 2018 he was co-founder of the spin-off ZenaByte s.r.l. He is currently Associate Professor in Computer Science at University of Pisa with particular interests in Statistical Learning Theory and Data Science. Besides being an editorial board member of the book series Modeling and Optimization in Science and Technologies he is also co-author of the textbook Introduction to Digital Systems Design (Donzellini et al., Springer, 2019). 

Table of contents (10 chapters)

Table of contents (10 chapters)

Buy this book

eBook 96,29 €
price for Spain (gross)
  • ISBN 978-3-030-24359-3
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 124,79 €
price for Spain (gross)
  • ISBN 978-3-030-24358-6
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 88,39 €
price for Spain (gross)
  • Due: August 8, 2020
  • ISBN 978-3-030-24361-6
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Model Selection and Error Estimation in a Nutshell
Authors
Series Title
Modeling and Optimization in Science and Technologies
Series Volume
15
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-24359-3
DOI
10.1007/978-3-030-24359-3
Hardcover ISBN
978-3-030-24358-6
Softcover ISBN
978-3-030-24361-6
Series ISSN
2196-7326
Edition Number
1
Number of Pages
XIII, 132
Number of Illustrations
62 b/w illustrations
Topics

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