Videos

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Localization schemes: A framework for proving mixing bounds for Markov chains Thumbnail

Localization schemes: A framework for proving mixing bounds for Markov chains

Presenter
  • Ronen Eldan
March 15, 2022
IAS
From geometry to topology: inverse theorems for distributed persistence Thumbnail

From geometry to topology: inverse theorems for distributed persistence

Presenter
  • Paul Bendich
April 16, 2021
IAS
Task-driven Network Discovery via Deep Reinforcement Learning on Embedded Spaces Thumbnail

Task-driven Network Discovery via Deep Reinforcement Learning on Embedded Spaces

Presenter
  • Tina Eliassi-Rad
February 25, 2021
IPAM
A rigorous and robust quantum speed-up in supervised machine learning Thumbnail

A rigorous and robust quantum speed-up in supervised machine learning

Presenter
  • Kristan Temme
February 9, 2021
IPAM
On Resilient Control for Secure Connected Vehicles Thumbnail

On Resilient Control for Secure Connected Vehicles

Presenter
  • Pierluigi Pisu
October 28, 2020
IPAM
Coarse graining autoencoders and evolutionary learning of atomistic potentials Thumbnail

Coarse graining autoencoders and evolutionary learning of atomistic potentials

Presenter
  • Rafael Gomez-Bombarelli
September 24, 2019
IPAM
High-dimensional Linear Regression for Dependent Observations with Application to Nowcasting Thumbnail

High-dimensional Linear Regression for Dependent Observations with Application to Nowcasting

Presenter
  • Ruey Tsay
April 23, 2018
IMA
Competing sources of variance reduction in parallel replica Monte Carlo, and optimization in the low temperature limit Thumbnail

Competing sources of variance reduction in parallel replica Monte Carlo, and optimization in the low temperature limit

Presenter
  • Paul Dupuis
November 16, 2017
IPAM
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II

Presenter
  • Russell Impagliazzo
November 14, 2017
IAS
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I

Presenter
  • Russell Impagliazzo
November 13, 2017
IAS
Crossing the logarithmic barrier for dynamic boolean data structure lower bounds Thumbnail

Crossing the logarithmic barrier for dynamic boolean data structure lower bounds

Presenters
  • Omri Weinstein
  • Omri Weinstein
October 2, 2017
IAS

Statistical Shape Analysis of 3D Objects using Square-Root Normal Fields

Presenter
  • Sebastian Kurtek
September 12, 2016
MBI