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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
Probing Moduli Space Cohomology Using Quantum Field Theory
Presenter
- Michael Borinsky
November 18, 2024
IAS
Michael Levin - Non-neural intelligence: biological architecture problem-solving in diverse spaces
Presenter
- Michael Levin
November 6, 2024
IPAM
Counting Representations of Fuchsian Groups Over Finite Fields
Presenter
- Michael Larsen
November 1, 2024
IAS
