
Ahlfors Lecture series
September 1112, 2018, Organizers: HT Yau and ST Yau
Harvard University, Science Center Hall D
Speaker and Program
Sanjeev Arora (Princeton University and Institute for Advanced Study)

September 11, 2018:
Lecture I 4:305:30 PM in SC Hall D

Lecture I:
"What is Machine Learning"
Abstract: Machine learning is the subfield of computer science concerned
with creating programs and machines that can improve from experience and
interaction. It relies upon mathematical optimization, statistics, and
algorithm design. The talk will be an introduction to machine learning
for a mathematical audience. We describe the mathematical formulations
of basic types of learning such as supervised, unsupervised, interactive,
etc., and the philosophical and scientific issues raised by them.

September 12, 2018:
Lecture II 3:304:30 PM in SC Hall D
 Lecture II:
"Toward Theoretical Understanding of Deep Learning"
Abstract: The empirical success of deep learning drives much of the
excitement about machine learning today. This success vastly outstrips our
mathematical understanding. This lecture surveys progress in recent years
toward developing a theory of deep learning. Works have started addressing
issues such as speed of optimization, sample requirements for training,
effect of architecture choices, and properties of deep generative models.

A reception follows the Tuesday lecture at 5:30 pm in
the Math Department common room.
