Undergraduate Seminar (395-0-31)

Instructors

Benjamin Weinkove
847 4915587
Lunt Hall 310 2033 Sheridan Road

Meeting Info

Lunt Hall 102: Mon, Wed, Fri 9:00AM - 9:50AM

Overview of class

Title: Mathematical Foundations of Neural Networks

Description: This is an undergraduate seminar on the mathematical foundations of neural networks. The course will cover topics including: the universal approximation theorem, the role of depth versus width,
quantitative approximation bounds, expressivity of neural networks, and measuring complexity of neural networks.

The seminar will focus on the rigorous mathematical theory of neural networks rather than their application. Guided by the instructor, students will be required to give oral presentations during class and complete a written project.

Prerequisites: Real analysis 320-1 or 321-1, or permission of the instructor.

Class Materials (Required)

No required materials.

Class Materials (Suggested)

No materials suggested.

Class Attributes

Advanced Expression

Enrollment Requirements

Enrollment Requirements: Registration in this course is reserved for students who are majoring or minoring in Mathematics.