Information Theoretic Learning Renyi's Entropy and Kernel Perspectives /

• Main Author: Principe, Jose C. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: New York, NY : Springer New York : Imprint: Springer, 2010.
• Series: Information Science and Statistics,
• Subjects: Computer science.; Computers.; Artificial intelligence.; Remote sensing.; Statistics.; Computational intelligence.; Computer Science.; Theory of Computation.; Artificial Intelligence (incl. Robotics).; Signal, Image and Speech Processing.; Computational Intelligence.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.; Remote Sensing/Photogrammetry.

This book presents the first cohesive treatment of Information Theoretic Learning (ITL) algorithms to adapt linear or nonlinear learning machines both in supervised or unsupervised paradigms. ITL is a framework where the conventional concepts of second order statistics (covariance, L2 distances, cor...