The Complexity of Learning Neural Networks

Over the past several years, we have seen many success stories in machine learning brought about by deep learning techniques. While the practical success of deep learning has been phenomenal, the formal guarantees have been lacking. Our current theoretical understanding of the many techniques that are central to the current ongoing big-data revolution is far from being sufficient for rigorous analysis, at best.

Guest

John Wilmes: Mathematician whose work included computational complexity and theoretical questions around neural-network learning.