Machine Learning for Multimedia Content Analysis / Edition 1

Machine Learning for Multimedia Content Analysis / Edition 1

by Yihong Gong, Wei Xu
     
 

ISBN-10: 0387699384

ISBN-13: 9780387699387

Pub. Date: 09/28/2007

Publisher: Springer US

This volume introduces machine learning techniques that are particularly powerful and effective for modeling multimedia data and common tasks of multimedia content analysis. It systematically covers key machine learning techniques in an intuitive fashion and demonstrates their applications through case studies. Coverage includes examples of unsupervised learning,

Overview

This volume introduces machine learning techniques that are particularly powerful and effective for modeling multimedia data and common tasks of multimedia content analysis. It systematically covers key machine learning techniques in an intuitive fashion and demonstrates their applications through case studies. Coverage includes examples of unsupervised learning, generative models and discriminative models. In addition, the book examines Maximum Margin Markov (M3) networks, which strive to combine the advantages of both the graphical models and Support Vector Machines (SVM).

Product Details

ISBN-13:
9780387699387
Publisher:
Springer US
Publication date:
09/28/2007
Series:
Multimedia Systems and Applications Series, #30
Edition description:
2007
Pages:
277
Product dimensions:
6.10(w) x 9.25(h) x 0.04(d)

Table of Contents

Unsupervised Learning.- Dimension Reduction.- Data Clustering Techniques.- Generative Graphical Models.- of Graphical Models.- Markov Chains and Monte Carlo Simulation.- Markov Random Fields and Gibbs Sampling.- Hidden Markov Models.- Inference and Learning for General Graphical Models.- Discriminative Graphical Models.- Maximum Entropy Model and Conditional Random Field.- Max-Margin Classifications.

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