Lecture Series in Pattern Recognition
题 目（TITLE）：Information Theoretic Learning
讲 座 人（SPEAKER）：Prof. Jose C. Principe, Distinguished Professor of Electrical Engineering, University of Florida
主 持 人 (CHAIR)：Prof. Baogang Hu
时 间 (TIME)：10:30AM, September 19 (Monday)
地 点 (VENUE)：The Second Meeting Room, 13th Floor
This talk describes our efforts to go beyond the second order moment assumption still prevalent in optimal signal processing. We show how the second norm of the PDF can be estimated directly from data avoiding an explicit PDF estimation step. The link between PDF moments, information theory and Reproducing Kernel Hilbert spaces will be established. Applications to adaptive systems with entropic cost functions will be demonstrated. A generalized correlation function called correntropy will be defined and its applications in signal processing will be outlined. Correntropy leads to new measures of similarity, to a new definition of dependence subspaces and to new tests for causality.
Jose C. Principe is Distinguished Professor of Electrical and Biomedical Engineering at the University of Florida, Gainesville, where he teaches advanced signal processing and machine learning. He is BellSouth Professor and Founding Director of the University of Florida Computational Neuro-Engineering Laboratory (CNEL). His research interests are centered in advanced signal processing and machine learning, Brain Machine Interfaces and the modeling and applications of cognitive systems. He has authored 5 books and more than 200 publications in refereed journals and book chapters, and over 380 conference papers. He has directed 65 Ph.D. dissertations and 67 Master's theses.
Dr. Principe is an IEEE and AIMBE Fellows a recipient of the INNS Gabor Award, the IEEE Engineering in Medicine and Biology Society Career Achievement Award, the IEEE Computational Intelligence Society Neural Network Pioneer Award, and Honorary doctor degrees from Universita Mediterranea, Italy, University of Maranhao Brasil, and Aalto University, Finland. He is Editor in Chief of the IEEE Reviews on Biomedical Engineering, Past Editor-in-Chief of the IEEE Transactions on Biomedical Engineering, current ADCOM member of the IEEE CIS society, IEEE Biometrics Council, and IEEE BME society, member of the Technical Committee on Machine Learning for Signal Processing of the IEEE Signal Processing Society; member of the Executive Committee of the International Neural Network Society, and Past President of the INNS. He is also a former member of the Scientific Board of the Food and Drug Administration, and a member of the Advisory Board of the McKnight Brain Institute at the University of Florida.