Intelligent Systems Reference Library

Hybrid Random Fields

A Scalable Approach to Structure and Parameter Learning in Probabilistic Graphical Models

Authors: Freno, Antonino, Trentin, Edmondo

  • Covers the concepts and techniques related to the hybrid random field model for the first time
  • Offers a self-contained introduction to semiparametric and nonparametric density estimation
  • Written by leading experts in the field
see more benefits

Buy this book

eBook 142,79 €
price for Spain (gross)
  • ISBN 978-3-642-20308-4
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 176,79 €
price for Spain (gross)
  • ISBN 978-3-642-20307-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 176,79 €
price for Spain (gross)
  • ISBN 978-3-642-26818-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Rent the eBook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
About this book

This book presents an exciting new synthesis of directed and undirected, discrete and continuous graphical models. Combining elements of Bayesian networks and Markov random fields, the newly introduced hybrid random fields are an interesting approach to get the best of both these worlds, with an added promise of modularity and scalability. The authors have written an enjoyable book---rigorous in the treatment of the mathematical background, but also enlivened by interesting and original historical and philosophical perspectives.
-- Manfred Jaeger, Aalborg Universitet

The book not only marks an effective direction of investigation with significant experimental advances, but it is also---and perhaps primarily---a guide for the reader through an original trip in the space of probabilistic modeling. While digesting the book, one is enriched with a very open view of the field, with full of stimulating connections. [...] Everyone specifically interested in Bayesian networks and Markov random fields should not miss it.
-- Marco Gori, Università degli Studi di Siena


Graphical models are sometimes regarded---incorrectly---as an impractical approach to machine learning, assuming that they only work well for low-dimensional applications and discrete-valued domains. While guiding the reader through the major achievements of this research area in a technically detailed yet accessible way, the book is concerned with the presentation and thorough (mathematical and experimental) investigation of a novel paradigm for probabilistic graphical modeling, the hybrid random field. This model subsumes and extends both Bayesian networks and Markov random fields. Moreover, it comes with well-defined learning algorithms, both for discrete and continuous-valued domains, which fit the needs of real-world applications involving large-scale, high-dimensional data.

Reviews

From the reviews:

“This book presents novel probabilistic graphical models, i.e., hybrid random fields. … the authors have written a very valuable book – rigorous in the treatment on the mathematical background, but also enriched with a very open view of the field, full of stimulating connections.” (Jerzy Martyna, zbMATH, Vol. 1278, 2014)

Table of contents (8 chapters)

  • Introduction

    Freno, Antonino (et al.)

    Pages 1-14

    Preview Buy Chapter 30,19 €
  • Bayesian Networks

    Freno, Antonino (et al.)

    Pages 15-41

    Preview Buy Chapter 30,19 €
  • Markov Random Fields

    Freno, Antonino (et al.)

    Pages 43-68

    Preview Buy Chapter 30,19 €
  • Introducing Hybrid Random Fields: Discrete-Valued Variables

    Freno, Antonino (et al.)

    Pages 69-86

    Preview Buy Chapter 30,19 €
  • Extending Hybrid Random Fields: Continuous-Valued Variables

    Freno, Antonino (et al.)

    Pages 87-119

    Preview Buy Chapter 30,19 €

Buy this book

eBook 142,79 €
price for Spain (gross)
  • ISBN 978-3-642-20308-4
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 176,79 €
price for Spain (gross)
  • ISBN 978-3-642-20307-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 176,79 €
price for Spain (gross)
  • ISBN 978-3-642-26818-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Rent the eBook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Hybrid Random Fields
Book Subtitle
A Scalable Approach to Structure and Parameter Learning in Probabilistic Graphical Models
Authors
Series Title
Intelligent Systems Reference Library
Series Volume
15
Copyright
2011
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer Berlin Heidelberg
eBook ISBN
978-3-642-20308-4
DOI
10.1007/978-3-642-20308-4
Hardcover ISBN
978-3-642-20307-7
Softcover ISBN
978-3-642-26818-2
Series ISSN
1868-4394
Edition Number
1
Number of Pages
XVIII, 210
Topics