Login

Principe, Jose C.

Information Theoretic Learning

Principe, Jose C. - Information Theoretic Learning, ebook

99,20€

Ebook, PDF with Adobe DRM
ISBN: 9781441915702
DRM Restrictions

PrintingNot allowed
Copy to clipboardNot allowed

Table of contents

1. Information Theory, Machine Learning, and Reproducing Kernel Hilbert Spaces
José C. Principe

2. Renyi’s Entropy, Divergence and Their Nonparametric Estimators
Dongxin Xu, Deniz Erdogmuns

3. Adaptive Information Filtering with Error Entropy and Error Correntropy Criteria
Deniz Erdogmus, Weifeng Liu

4. Algorithms for Entropy and Correntropy Adaptation with Applications to Linear Systems
Deniz Erdogmus, Seungju Han, Abhishek Singh

5. Nonlinear Adaptive Filtering with MEE, MCC, and Applications
Deniz Erdogmus, Rodney Morejon, Weifeng Liu

6. Classification with EEC, Divergence Measures, and Error Bounds
Deniz Erdogmus, Dongxin Xu, Kenneth Hild

7. Clustering with ITL Principles
Robert Jenssen, Sudhir Rao

8. Self-Organizing ITL Principles for Unsupervised Learning
Sudhir Rao, Deniz Erdogmus, Dongxin Xu, Kenneth Hild

9. A Reproducing Kernel Hilbert Space Framework for ITL
Jianwu Xu, Robert Jenssen, Antonio Paiva, Il Park

10. Correntropy for Random Variables: Properties and Applications in Statistical Inference
Weifeng Liu, Puskal Pokharel, Jianwu Xu, Sohan Seth

11. Correntropy for Random Processes: Properties and Applications in Signal Processing
Puskal Pokharel, Ignacio Santamaria, Jianwu Xu, Kyu-hwa Jeong, Weifeng Liu

Keywords: Engineering, Signal, Image and Speech Processing, Computational Intelligence, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Remote Sensing/Photogrammetry

Author(s)
Publisher
Springer
Publication year
2010
Language
en
Edition
1
Series
Information Science and Statistics
Page amount
22 pages
Category
Technology, Energy, Traffic
Format
Ebook
eISBN (PDF)
9781441915702

Similar titles