Probabilistic Graphical Models

Principles and Applications

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Application Software, General Computing
Cover of the book Probabilistic Graphical Models by Luis Enrique Sucar, Springer London
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Luis Enrique Sucar ISBN: 9781447166993
Publisher: Springer London Publication: June 19, 2015
Imprint: Springer Language: English
Author: Luis Enrique Sucar
ISBN: 9781447166993
Publisher: Springer London
Publication: June 19, 2015
Imprint: Springer
Language: English

This accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. Features: presents a unified framework encompassing all of the main classes of PGMs; describes the practical application of the different techniques; examines the latest developments in the field, covering multidimensional Bayesian classifiers, relational graphical models and causal models; provides exercises, suggestions for further reading, and ideas for research or programming projects at the end of each chapter.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. Features: presents a unified framework encompassing all of the main classes of PGMs; describes the practical application of the different techniques; examines the latest developments in the field, covering multidimensional Bayesian classifiers, relational graphical models and causal models; provides exercises, suggestions for further reading, and ideas for research or programming projects at the end of each chapter.

More books from Springer London

Cover of the book Introduction to Biopsy Interpretation and Surgical Pathology by Luis Enrique Sucar
Cover of the book The Etiology of Atopic Dermatitis by Luis Enrique Sucar
Cover of the book Stochastic Reliability and Maintenance Modeling by Luis Enrique Sucar
Cover of the book Control of Noise and Structural Vibration by Luis Enrique Sucar
Cover of the book Dynamics and Control of Mechanical Systems in Offshore Engineering by Luis Enrique Sucar
Cover of the book Self-* and P2P for Network Management by Luis Enrique Sucar
Cover of the book Histopathology Specimens by Luis Enrique Sucar
Cover of the book Performance Metrics for Haptic Interfaces by Luis Enrique Sucar
Cover of the book Manual of Heart Failure Management by Luis Enrique Sucar
Cover of the book Coronary Artery Disease by Luis Enrique Sucar
Cover of the book Commercial-Industrial Cleaning, by Pressure-Washing, Hydro-Blasting and UHP-Jetting by Luis Enrique Sucar
Cover of the book Guide to Pediatric Urology and Surgery in Clinical Practice by Luis Enrique Sucar
Cover of the book 3D Computer Vision by Luis Enrique Sucar
Cover of the book Game Analytics by Luis Enrique Sucar
Cover of the book Social Interaction, Globalization and Computer-Aided Analysis by Luis Enrique Sucar
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy