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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
Hot Topics: Interactions between Harmonic Analysis, Homogeneous Dynamics, and Number Theory: Toral endomorphisms and equidistribution
Presenter
- Michael Hochman
March 5, 2025
SLMath
Exacting Approximate Graph Representations, or How to Avoid Comp-Bio Hazards by Cleaning Your Filters
Presenters
- Michael Bender
- Rob Johnson
February 21, 2025
ICERM
Michael DiPasquale - Generalized Hamming weights & symbolic powers of Stanley-Reisner ideal matroids
Presenter
- Michael DiPasquale
February 13, 2025
IPAM
Low-Depth Algebraic Circuit Lower Bounds Over Any Field
Presenter
- Michael Forbes
February 3, 2025
IAS
Michael Le Bars - Interplay of Boundary and Bulk Dynamics in Rotating Turbulence Driven by Libration
Presenter
- Michael Le Bars
January 31, 2025
IPAM
Michael Calkins - Scaling laws and force balances in rotating convection: are they consistent?
Presenter
- Michael Calkins
January 28, 2025
IPAM