Videos

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Approximating Likelihoods for Spatial Extremes with Deep Learning Thumbnail

Approximating Likelihoods for Spatial Extremes with Deep Learning

Presenter
  • Reetam Majumder
October 4, 2022
IMSI
A Fast and Programmable Accelerator for Fully Homomorphic Encryption Thumbnail

A Fast and Programmable Accelerator for Fully Homomorphic Encryption

Presenter
  • Daniel Sanchez
February 7, 2022
IMSI
Learning from data under information constraints: Fundamental limits and applications Thumbnail

Learning from data under information constraints: Fundamental limits and applications

Presenter
  • Jayadev Acharya
April 14, 2021
IMSI

Metric representations - Algorithms and Geometry

Presenter
  • Anna Gilbert
April 21, 2020
ICERM
Kernel and Rich Regimes in Deep Learning Thumbnail

Kernel and Rich Regimes in Deep Learning

Presenter
  • Nati Srebro
October 17, 2019
IAS
Robustness and Strategic Concerns in Machine Learning Thumbnail

Robustness and Strategic Concerns in Machine Learning

Presenter
  • Yu Cheng
September 24, 2019
IAS
Deep Learning Opening Workshop: Statistical and Computational Guarantees of EM with Random Initialization, Harrison Zhou Thumbnail

Deep Learning Opening Workshop: Statistical and Computational Guarantees of EM with Random Initialization, Harrison Zhou

August 12, 2019
SAMSI

Bayesian nonparametrics and g-computation for causal inference in observational studies

Presenter
  • Jason Roy
January 15, 2019
ICERM
Machine learning methods for physics and chemistry 2: Deep learning Thumbnail

Machine learning methods for physics and chemistry 2: Deep learning

Presenter
  • Frank Noé
September 15, 2017
IPAM
Machine learning methods for physics and chemistry 1: Regression and Kernel methods Thumbnail

Machine learning methods for physics and chemistry 1: Regression and Kernel methods

Presenter
  • Frank Noé
September 15, 2017
IPAM
Delay and Cooperation in Nonstochastic Bandits Thumbnail

Delay and Cooperation in Nonstochastic Bandits

Presenter
  • Nicolo Cesa-Bianchi
May 17, 2016
IMA
Practically Relevant Theory and Theoretically Relevant Practice of Deep Learning Thumbnail

Practically Relevant Theory and Theoretically Relevant Practice of Deep Learning

Presenter
  • Shai Shalev-Shwartz
May 17, 2016
IMA