[talks] last reminder: CS Colloquium (TODAY): Stuart Geman]

[Fei-Fei Li]

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Dear all,

Stuart Geman, James Manning Professor of Applied Mathematics from Brown
University, will give a CS Colloquium talk at 4:15pm TODAY in the CS 
Small Auditorium.
Prof. Geman has been a leader in statistics and computer vision. His
recent projects span from computer vision to neuroscience to financial
markets. Below please find his talk title and abstracts.

Fei-Fei

Google and the Vapnik-Chervonenkis Dimension

Stuart Geman
Brown University

Google engineers routinely train query classifiers, for ranking
advertisements or search results, on more words than any human being
sees or hears in a lifetime. A human being who sees a meaningfully new
image every second for one-hundred years will not see as many images as
Google has in its libraries, all of which are available for training
object detectors and image classifiers. Yet by human standards the
state-of-the-art, in computer understanding of language and
computer-generated image analysis, is primitive. What explains the gap?
Why can’t learning theory tell us how to make machines that learn as
efficiently as humans? Upper bounds on the number of training samples
needed to learn a classifier as rich and competent as the human visual
system can be derived using the Vapnik-Chervonenkis dimension, or the
metric entropy, but these suggest that not only does Google need more
examples, but all of evolution might fall short. I will make some
proposals for efficient learning and offer some mathematics to support
them.
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Li, Fei-Fei     Ph.D.
(publish under L. Fei-Fei)
Assistant Professor
Computer Science Dept.
Princeton University
35 Olden St.
Princeton, NJ 08540

Tel: (609)258-8130
Office: Room 411, CS Building
Website: http://vision.cs.princeton.edu
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