Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision
From Bits to Information: Theory and Applications of Learning
Machines
Tomaso Poggio
Center for Biological and Computational Learning
AI Laboratory and McGovern Institute for Brain Research
MIT
Monday, Dec 4, 2000, 4:15PM
TCseq200, Lecture Hall A
http://robotics.stanford.edu/ba-colloquium/
Abstract
Learning is becoming the central problem in trying to understand
intelligence and in trying to develop intelligent machines. I will
outline some of our recent efforts in developing machines that learn.
I will sketch our work on statistical learning theory and recent
theoretical results on the problem of classification and function
approximation that connect regularization theory and Support
Vector Machines. Our main application focus is classification
(and regression) in various domains -- such as sound, text, video
and bioinformatics. In particular, I will describe the recent evolution
of a trainable object detection system for classifying objects --
such as faces and people and cars -- in complex cluttered images.
Finally, I will speculate on the implications of this research for how
the brain works and review some recent data which provide a glimpse
of how visual cortex learns to identify and classify 3D objects.
About the Speaker
Professor Tomaso Poggio is the Uncas and Helen Whitaker Professor in the
Department of Brain and Cognitive Sciences at MIT, where he directs
research in machine learning, computer vision and neuroscience at the
MIT Artificial Intelligence Laboratory and at the MIT Center for
Biological and Computational Learning.
Known for his work on the visual system of the fly, nonlinear systems
theory, stereo vision and for introducing regularization theory in
computer vision, Professor Poggio and his group have spent the past ten
years developing a theory of networks for learning in the framework of
multivariate function approximation and applying them to several
different domains from signal processing to multimedia database search,
from finance to bioinformatics, from computer graphics to computer
vision for object detection and recognition. He has also contributed to
models of the brain and most recently to models of IT cortex for object
recognition that are supported in the meantime by physiological data.
Co-Director, since 1992, of CBCL, the Center for Biological and
Computational Learning at MIT, Professor Poggio is the author of
numerous papers in areas ranging from psychophysics and biophysics to
information processing in man and machine, artificial intelligence,
machine vision and learning. Serving on the editorial boards of a
number of leading interdisciplinary journals, Professor Poggio is a
member of the American Academy of Arts and Sciences, a Fellow of the
American Association for Artificial Intelligence, and an Honorary
Associate of the Neuroscience Research Program at Rockefeller
University. Professor Poggio received his doctorate in theoretical
physics from the University of Genoa in 1970, had a tenured research
position at the Max Planck Institute from 1971 to 1981 when he became
Professor at MIT. In the years since then, he has received a number of
distinguished international awards in the scientific community. A former
Corporate Fellow of Thinking Machines Corporation, he has been involved
in several companies in the areas of computer graphics, computer vision,
computer networks, financial engineering and bioinformatics.
bac-coordinators@cs.stanford.edu
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Last modified: Thu Oct 19 18:18:43 PST 2000