# VC-theory

Tuesday, February 2, 2016 - 1:25pm - 2:25pm

Vladimir Cherkassky (University of Minnesota, Twin Cities)

Vapnik-Chervonenkis theory (VC-theory), aka Statistical Learning Theory, provides a mathematical framework for predictive data-analytic modeling in machine learning, statistics, data mining, signal processing, bioinformatics etc. The VC-theory was developed in the 1970’s in the former USSR, but it became widely known only in mid-1990’s after introduction of Support Vector Machines. Even though the VC-theory is widely known as a mathematical theory, its methodological contributions are not well known or appreciated.