The University of Arizona

An Invitation to Machine Learning for Pure and Applied Mathematicians

An Invitation to Machine Learning for Pure and Applied Mathematicians

Series: Modeling and Computation Seminar
Location: Math 402
Presenter: Sivaguru Sritharan, Wright Patterson Air Force Base, Air Force Institute of Technology, and Program in Applied Mathematics Alumni, (PhD 1982)

Machine learning is rapidly evolving as a powerful tool in enhancing computational physics, pattern recognition, artificial intelligence, etc.  In this talk we will first describe some of the basic elements of the theory of statistical learning by V. N. Vapnik and A. Chervonenkis such as support vector machine, reproducing kernel methods etc. We will then indicate possible future directions in connecting these developments to some of the latest results in statistical and stochastic Navier-Stokes equations such as invariant-ergodic measures, martingale solutions, nonlinear stochastic filtering and large deviations (all deal with the probability laws of fluid velocity), with the long term vision of developing machine learning to turbulence.

Department of Mathematics, The University of Arizona 617 N. Santa Rita Ave. P.O. Box 210089 Tucson, AZ 85721-0089 USA Voice: (520) 621-6892 Fax: (520) 621-8322 Contact Us © Copyright 2019 Arizona Board of Regents All rights reserved