Machine Learning Seminar Series

Location: ED 612

Speaker: Amitabh Halder, University of Regina

Title: Universal Approximation Theorem

Abstract:

Amitabh Halder will present a proof of the Universal Approximation Theorem, which states that a feedforward neural network with a single hidden layer and a finite number of neurons can approximate any continuous function on a compact set with appropriate activation functions.