[Colloquium] 1/24 Talk at TTIC: Steve Hanneke, TTIC

[Jerome Allen]

*When:     Friday, January 24th at 10:30am*



*Where:*    TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526



*Who: *      Steve Hanneke, TTIC

*Title:*  Learning Whenever Learning is Possible: Universal Learning under
General Stochastic Processes

*Abstract:*
I will present a general theory of learning and generalization without the
i.i.d. assumption, starting from first principles. We focus on the problem
of universal consistency: the ability to estimate any function from X to Y.
We endeavor to answer the question: Does there exist a learning algorithm
that is universally consistent under every process on X for which universal
consistency is possible? Remarkably, we find the answer is "Yes". Thus, we
replace the i.i.d. assumption with only the most natural (and necessary!)
assumption: that learning is at least possible. Along the way, we also find
a concise characterization of the family of all processes that admit
universally consistent learners. One challenge for learning is that some of
these processes do not even have a law of large numbers.

*Bio:*
Steve Hanneke is a Research Assistant Professor at the Toyota Technological
Institute at Chicago. His research explores the theory of machine learning,
with a focus on reducing the number of training examples sufficient for
learning. His work develops new approaches to supervised, semi-supervised,
transfer, and active learning, and also revisits the basic probabilistic
assumptions at the foundation of learning theory. Steve earned a Bachelor
of Science degree in Computer Science from UIUC in 2005 and a Ph.D. in
Machine Learning from Carnegie Mellon University in 2009 with a
dissertation on the theoretical foundations of active learning.

*Host: Brian Bullins*


*Jerome Allen*
Executive Assistant
*Toyota Technological Institute*
6045 S. Kenwood Avenue
Room 518
Chicago, IL  60637
p:(773) 702-2311
*jallen at ttic.edu <jallen at ttic.edu>*
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