MALBEC lecture by Partha Niyogi
Geometry, Perception and Learning
Event Details
Date
Friday, April 17, 2009
Time
4 p.m.
Location
B102 Van Vleck Hall
Description
Our perceptual systems (visual and auditory) are confronted with data
in very high dimensional spaces. Yet we are able to learn how to
recognize faces, objects, phonemes, words and so on without running
into the "curse of dimensionality." How might we get machines to
replicate this ability? What might be plausible principles of learning
in high dimensional spaces and what is its relevance to biological
learning?
in very high dimensional spaces. Yet we are able to learn how to
recognize faces, objects, phonemes, words and so on without running
into the "curse of dimensionality." How might we get machines to
replicate this ability? What might be plausible principles of learning
in high dimensional spaces and what is its relevance to biological
learning?
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Cost
Free
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