Learning Theory and Problems of Statistics
Date and Time
Wednesday, April 3, 2002 - 4:00pm to 5:30pm
Computer Science Small Auditorium (Room 105)
Vladimir Vapnik, from NEC Research Institute
In this talk I will discuss the main principles of inference from data developed in statistical learning theory which consider in non-parametric framework the problem of inference from a given (fixed) sample size.
Along with a survey of new ideas of statistical learning theory and their comparison to classical statistical approaches, I will discuss the problem of constructing learning machines that implement these new ideas.