Videos

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From clustering with graph cuts to isoperimetric inequalities: quantitative convergence rates of Cheeger cuts on data clouds Thumbnail

From clustering with graph cuts to isoperimetric inequalities: quantitative convergence rates of Cheeger cuts on data clouds

Presenter
  • Nicolas Garcia Trillos
April 24, 2020
IPAM
Learning with few labeled data Thumbnail

Learning with few labeled data

Presenter
  • Pratik Chaudhari
April 23, 2020
IPAM
Learning Over-parameterized Neural Networks: From Neural Tangent Kernel to Mean-field Analysis Thumbnail

Learning Over-parameterized Neural Networks: From Neural Tangent Kernel to Mean-field Analysis

Presenter
  • Quanquan Gu
April 23, 2020
IPAM
Learning to Solve Inverse Problems in Imaging Thumbnail

Learning to Solve Inverse Problems in Imaging

Presenter
  • Rebecca Willett
April 23, 2020
IPAM
Training neural ODEs for density estimation Thumbnail

Training neural ODEs for density estimation

Presenter
  • Christopher Finlay
April 23, 2020
IPAM
Accelerated Information Gradient Flow Thumbnail

Accelerated Information Gradient Flow

Presenter
  • Wuchen Li
April 23, 2020
IPAM
An empirical look at generalization in neural nets Thumbnail

An empirical look at generalization in neural nets

Presenter
  • Tom Goldstein
April 22, 2020
IPAM
Differential Operators for Generating Structured Adversarial Examples Thumbnail

Differential Operators for Generating Structured Adversarial Examples

Presenter
  • Hossein Mobahi
April 22, 2020
IPAM
Accelerated Optimization in the PDE Framework Thumbnail

Accelerated Optimization in the PDE Framework

Presenter
  • Anthony Yezzi
April 22, 2020
IPAM
The joint power of deterministic and Bayesian approaches for seismic inverse problems Thumbnail

The joint power of deterministic and Bayesian approaches for seismic inverse problems

Presenter
  • Yunan Yang
April 22, 2020
IPAM
Rank optimality of the Burer-Monteiro factorization Thumbnail

Rank optimality of the Burer-Monteiro factorization

Presenter
  • Irene Waldspurger
April 22, 2020
IPAM
Toward a theory of optimization for over-parameterized systems of non-linear equations: the lessons of deep learning Thumbnail

Toward a theory of optimization for over-parameterized systems of non-linear equations: the lessons of deep learning

Presenter
  • Mikhail Belkin
April 21, 2020
IPAM