The role of Random Matrix Theory for the optimization algorithms of Machine Learning

Add to your list(s) Download to your calendar using vCal

• Gérard Ben Arous (Courant)
• Thursday 12 March 2026, 16:30-17:30
• Centre for Mathematical Sciences MR2.

If you have a question about this talk, please contact Richard Samworth.

I will survey recent progress in the understanding of the optimization dynamics for important tasks for Machine Learning or high dimensional statistics. We will see how these very high-dimensional dynamics are in fact ruled by the so-called “effective dynamics” of much lower dimensional systems. This dynamical dimension reduction is related to the BBP spectral transition of Random Matrix Theory, appearing dynamically along the algorithm path. I will illustrate these phenomena in multi-spike Tensor PCA , XOR, and classification of Gaussian mixtures with multi-layer neural nets.

This talk is based on joint works with Reza Gheissari (Northwestern), Jiaoyang Huang (Wharton), Aukosh Jagannath (Waterloo), and on joint works with Cedric Gerbelot (ENS Lyon) and Vanessa Piccolo (EPFL).

A wine reception in the Central Core will follow the lecture.

This talk is part of the Peter Whittle Lecture series.

This talk is included in these lists:

• All CMS events
• All Talks (aka the CURE list)
• CMS Events
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge talks
• Centre for Mathematical Sciences MR2
• Chris Davis' list
• DAMTP Departmental Seminar
• DAMTP info aggregator
• DPMMS Lists
• DPMMS info aggregator
• DPMMS lists
• Faculty of Mathematics Lectures
• Guy Emerson's list
• Hanchen DaDaDash
• Interested Talks
• Machine Learning
• Peter Whittle Lecture
• Probability
• School of Physical Sciences
• Statistical Laboratory info aggregator
• Statistics
• Statistics Group
• bld31
• custom
• ndb35's list
• rp587

Note that ex-directory lists are not shown.