Introduction to the Theory of Neural Networks

This lecture gives an introduction to neural network learning from a theoretical standpoint. The main focus is on supervised learning problems, covering topics on learnability, generalization, and complexity. The lecture will also touch on current developments on the theory of deep learning.

References
M. Anthony and P. Bartlett, Neural Network Learning: Theoretical Foundations, Part one.

Date and time info
Thursday 11:15 - 12:45

Keywords
artificial neural networks, supervised learning, pattern classification, VC-dimension, theory of deep learning

Prerequisites
basic linear algebra and analysis

Audience
MSc students, PhD students, Postdocs

Language
English