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home · events · colloquia · 1997-1998 · 

Colloquium - Kearns

ECCR 265

Quantifying Induction: Some Recent Developments in the Theory of Machine Learning
AT&T Laboratories Research
Michael Kearns photo

The exchange of ideas between theoreticians and practitioners of machine learning has risen dramatically in the last decade. In this talk, I will sketch developments in two of the topics in which this cross-fertilization has been the most effective and interesting: the study of learning curves, which quantifies the rate at which a learning algorithm generalizes from empirical data, and the framework known as boosting, which has led to the discovery of new algorithms and shed light on some classical heuristics. Along the way, I will highlight some of the many areas that have had direct and powerful impact on modern machine learning, including information theory, statistical mechanics, and combinatorics.

Refreshments will be served immediately before the talk at 3:30pm.
Hosted by Satinder Singh.

The Department holds colloquia throughout the Fall and Spring semesters. These colloquia, open to the public, are typically held on Thursday afternoons, but sometimes occur at other times as well. If you would like to receive email notification of upcoming colloquia, subscribe to our Colloquia Mailing List. If you would like to schedule a colloquium, see Colloquium Scheduling.

Sign language interpreters are available upon request. Please contact Stephanie Morris at least five days prior to the colloquium.

See also:
Department of Computer Science
College of Engineering and Applied Science
University of Colorado Boulder
Boulder, CO 80309-0430 USA
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