The approximation power of neural networks [1 ECTS MATH-05]

Speaker
Leonard P. Bos - University of Calgary

Date
Apr 20, 2026 - Time: 12:30 Aula H (see full schedule)

Neural Nets generate outputs according to a specific recipe, i.e., they form a certain family of (vector valued) functions, determined by a typically large number of parameters (the weights). Training a Neural Net means to adjust the parameters to produce a desired output, i.e., find a good approximation to a given output function from the family of functions produced by the Net.
In this course we will explore, in relation to classical approximation by polynomials and splines, how good an approximation can be so obtained.
The course will be completely self contained.

Schedule

  • Monday 20/04/2026  12:30-13:30,  Room H
  • Thursday 23/04/2026  10:30-12:30,  Room H
  • Friday 24/04/2026 10:30-12:30, Room M
  • Monday 27/04/2026  12:30-13:30,  Room H

More information: giacomo.albi@univr.it

Data pubblicazione
Mar 2, 2026

Contact person
Giacomo Albi
Department
Computer Science