Lecture Series in Pattern Recognition
题 目（TITLE）：On-Line Kernel Learning
讲 座 人（SPEAKER）：Jose C. Principe, Distinguished Professor of Electrical Engineering, University of Florida
主 持 人 (CHAIR)：Prof. Baogang Hu
时 间 (TIME)：14:00PM, September 21 (Wednesday)
地 点 (VENUE)：The Second Meeting Room, 13th Floor
This talk will summarize recent advances in nonlinear adaptive filtering. Designing adaptive filters in Reproducing Kernel Hilbert Spaces (RKHS) bridges the established procedures of adaptive filter theory with kernel methods. The end result is a family of filters that are universal approximators in the input space, that have convex performance surfaces (no local minima), and that are on-line, i.e. they adapt with every new sample of the input. Moreover, we will show that contrary to common believe some of its members do not need explicit regularization, e.g. the Kernel Least Mean Squares (KLMS) is well posed in the sense of Hadamard. They are however growing structures therefore special techniques need to be included to curtail their growth. Although the tutorial will focus on adaptive filtering, similar techniques can be applied to the kernel algorithms of machine learning.
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.