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Machine Learning: A Constraint-Based Approach
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Marco Gori (Department of Information Engineering and Mathematics, University of Siena, Italy)
Machine Learning: A Constraint-Based Approach by Marco Gori (Department of Information Engineering and Mathematics, University of Siena, Italy) at Abbey's Bookshop,

Machine Learning: A Constraint-Based Approach

Marco Gori (Department of Information Engineering and Mathematics, University of Siena, Italy)


9780081006597

Morgan Kaufmann


Machine learning;
Computer vision


Paperback

580 pages

$117.95
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Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines.

The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. While regarding symbolic knowledge bases as a collection of constraints, the book draws a path towards a deep integration with machine learning that relies on the idea of adopting multivalued logic formalisms, like in fuzzy systems. A special attention is reserved to deep learning, which nicely fits the constrained- based approach followed in this book.

This book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, and includes many solved exercises that are classified according to the Donald Knuth ranking of difficulty, which essentially consists of a mix of warm-up exercises that lead to deeper research problems. A software simulator is also included.

By:   Marco Gori (Department of Information Engineering and Mathematics University of Siena Italy)
Imprint:   Morgan Kaufmann
Country of Publication:   United Kingdom
Dimensions:   Height: 235mm,  Width: 191mm, 
Weight:   810g
ISBN:   9780081006597
ISBN 10:   0081006594
Pages:   580
Publication Date:   November 2017
Audience:   College/higher education ,  Primary
Format:   Paperback
Publisher's Status:   Active

The Big Picture Learning Principles Linear-Threshold Machines Kernel Machines Deep Architectures Learning and Reasoning with Constraints Epilogue Answers to selected exercises Appendices: Constrained optimization in Finite Dimensions Regularization operators Calculus of variations Index to Notations

Professor Gori's research interests are in the field of artificial intelligence, with emphasis on machine learning and game playing. He is a co-author of the book Web Dragons: Inside the myths of search engines technologies, Morgan Kauffman (Elsevier), 2007. He was the Chairman of the Italian Chapter of the IEEE Computational Intelligence Society, and the President of the Italian Association for Artificial Intelligence. He is in the list of top Italian scientists kept by VIAAcademy(http://www.topitalianscientists.org/top_italian_scientists.aspx). Dr. Gori is a fellow of the IEEE, ECCAI, and IAPR.


  • Winner of <p> The book is highly recommended for a machine learning course or self study from the statistical perspective that is based on constraint-based environments. <b>-Zentralblatt MATH</p></b>.
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