Start date cannot be after end date.
Recent Developments in RandNLA: Random Matrix Theory for Modern Machine Learning?
Presenter
- Michael Mahoney
February 2, 2026
ICERM
Why Deep Learning Works: Heavy-Tailed Random Matrix Theory as an Example of Physics Informed Machine Learning
Presenter
- Michael Mahoney
October 14, 2019
IPAM
Eigenvector Localization, Implicit Regularization, and Algorithmic Anti-differentiation for Large-scale Graphs and Networked Data
Presenter
- Michael Mahoney
April 30, 2014
IMA
Extracting insight from large networks: small-scale structures, large-scale structures, and their implications for machine learning and data analysis
Presenter
- Michael Mahoney
October 25, 2011
IMA
Extracting insight from large networks: small-scale structures, large-scale structures, and their implications for machine learning and data analysis
Presenter
- Michael Mahoney
October 25, 2011
IMA
Hyperbolicity: Evaluation and Connections with other Tree-like Structure
Presenter
- Blair Sullivan
April 28, 2014
IMA
Eigenvector localization, implicit regularization, and algorithmic anti-differentiation for large-scale graphs and networked data
Presenter
- Michael W. Mahoney
May 6, 2014
ICERM
Michael Perlmutter - The Geometric Scattering Transform for High-dimensional Data Analysis
Presenter
- Michael Perlmutter
February 26, 2026
IPAM
Michael Beverland - Real-time decoding for fault-tolerant quantum computers - IPAM at UCLA
Presenter
- Michael Beverland
February 19, 2026
IPAM
Michael Fischer - Machine Learning Approach to Estimate 3-D Tropical Cyclone Kinematic Structure
Presenter
- Michael Fischer
February 4, 2026
IPAM
Michael Ghil - Global warming & global weirding: Nonautonomous dynamics for chaotic & noisy systems
Presenter
- Michael Ghil
February 2, 2026
IPAM
