eBook Machine Learning: A Constraint-Based Approach, 1st Edition

  • Marco Gori
  • Published By: Morgan Kaufmann
  • ISBN-10: 0081006705
  • ISBN-13: 9780081006702
  • DDC: 006.31
  • Grade Level Range: 11th Grade - College Senior
  • 580 Pages | eBook
  • Original Copyright 2018 | Published/Released May 2018
  • This publication's content originally published in print form: 2018
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About

Overview

This book 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. It 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.

Table of Contents

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Dedication.
Contents.
Preface.
Notes on the Exercises.
1: The Big Picture.
2: Learning Principles.
3: Linear Threshold Machines.
4: Kernel Machines.
5: Deep Architectures.
6: Learning and Reasoning with Constraints.
7: Epilogue.
8: Answers to Exercises.
Appendix A Constrained Optimization in Finite Dimensions.
Appendix B Regularization Operators.
Appendix C Calculus of Variations.
Appendix D Index to Notation.
Bibliography.
Index.