Boltzmann machines

September 17 to September 21, 2018

at the

American Institute of Mathematics, San Jose, California

organized by

Asja Fischer, Guido Montufar, and Jason Morton

Original Announcement

This workshop will be devoted to the mathematics of Boltzmann machines. Since their debut in the context of deep learning, Boltzmann machines have been studied intensively, with significant leaps over the past six years, giving them a rare combination of mathematical traction and practical machine learning relevance. Researchers have been pushing tools in information theory, algebra, combinatorics, geometry, and optimization to their limits to achieve the understanding we currently have of these models. The result is a situation where further progress probably requires a more intimate merger of these tools.

The workshop will analyze Boltzmann machines in terms of

Advancing on these topics will, so we hope, open new avenues to study probabilistic graphical models with hidden variables in general, and contribute to the mathematical foundations of machine learning.

Material from the workshop

A list of participants.

The workshop schedule.

A report on the workshop activities.

Workshop Videos