Abstract
Information Theory
Ying Nian Wu
University of California, Los Angeles (UCLA)
This talk reviews the basic concepts in information theory and information-theoretical principles for statistical modeling. I will first explain the concepts of entropy and Kullback-Leibler divergence. Then I will describe an information-geometrical point of view for model updating in learning.
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