Alex Iosevich, U Rochester
3:45 PM - 4:45 PM
The notion of the Vapnik-Chervonenkis dimension first arose in learning theory and is a part of the foundation of the theory behind machine learning and related concepts. The VC-dimensional has also found fruitful applications in combinatorics where it is both to prove concrete theorems and to provide a complexity framework for the existing notions. In this talk, we are going to discuss the VC dimension in the context of the existence of finite point configurations in subsets of vector spaces over finite fields.
Event contact: dinesh dot thakur at rochester dot edu