Structured Regularization Summer School - 19-22/06/2017 | Tag

Compressed Sensing: Structure and Imaging 1

01:34:46

published on June 21, 2017

Compressed Sensing: Structure and Imaging 1

By Anders Hansen

Compressed Sensing: Structure and Imaging 2

01:27:40

published on June 21, 2017

Compressed Sensing: Structure and Imaging 2

By Anders Hansen

On Foundational Computational Problems in l1 and Total Variation Regularisation 3

01:31:14

published on June 22, 2017

On Foundational Computational Problems in l1 and Total Variation Regularisation 3

By Anders Hansen

On Foundational Computational Problems in l1 and Total Variation Regularisation 4

01:24:26

published on June 22, 2017

On Foundational Computational Problems in l1 and Total Variation Regularisation 4

By Anders Hansen

01:34:23

published on June 21, 2017

Matrix and graph estimation 1

By Andrea Montanari

01:27:14

published on June 22, 2017

Matrix and graph estimation 2

By Andrea Montanari

01:32:20

published on June 22, 2017

Matrix and graph estimation 3

By Andrea Montanari

01:29:45

published on June 26, 2017

Matrix and graph estimation 4

By Andrea Montanari

Submodular Functions: from Discrete to Continuous Domains

01:04:15

published on June 22, 2017

Submodular Functions: from Discrete to Continuous Domains

By Francis Bach

A sampling theorem for robust deconvolution

01:01:37

published on June 22, 2017

A sampling theorem for robust deconvolution

By Carlos Fernandez-Granda

Majorization-Minimization Subspace Algorithms for Large Scale Data Processing

01:07:15

published on June 23, 2017

Majorization-Minimization Subspace Algorithms for Large Scale Data Processing

By Emilie Chouzenoux

01:09:14

published on June 26, 2017

Towards realistic compressed sensing

By Claire Boyer

Regularization Methods for Large Scale Machine Learning 1

01:36:27

published on June 23, 2017

Regularization Methods for Large Scale Machine Learning 1

By Lorenzo Rosasco

Regularization Methods for Large Scale Machine Learning 2

01:29:38

published on June 23, 2017

Regularization Methods for Large Scale Machine Learning 2

By Lorenzo Rosasco

Regularization Methods for Large Scale Machine Learning 3

01:38:19

published on June 26, 2017

Regularization Methods for Large Scale Machine Learning 3

By Lorenzo Rosasco

Regularization Methods for Large Scale Machine Learning 4

01:23:30

published on June 26, 2017

Regularization Methods for Large Scale Machine Learning 4

By Lorenzo Rosasco

Mathematics
and Interactions

2025 IHES Summer School – Statistical Aspects of Nonlinear Physics

Mathematics for an by Large Language Models – 2025 Edition

Fuzzy Sphere Meets Conformal Bootstrap 2025

Physics and Mathematics of hydrodynamic and wave turbulence / Physique et Mathématiques de la turbulence hydrodynamique et de la turbulence d'ondes

Collection Structured Regularization Summer School - 19-22/06/2017

Compressed Sensing: Structure and Imaging 1

Compressed Sensing: Structure and Imaging 2

On Foundational Computational Problems in l1 and Total Variation Regularisation 3

On Foundational Computational Problems in l1 and Total Variation Regularisation 4

Matrix and graph estimation 1

Matrix and graph estimation 2

Matrix and graph estimation 3

Matrix and graph estimation 4

Submodular Functions: from Discrete to Continuous Domains

A sampling theorem for robust deconvolution

Majorization-Minimization Subspace Algorithms for Large Scale Data Processing

Towards realistic compressed sensing

Regularization Methods for Large Scale Machine Learning 1

Regularization Methods for Large Scale Machine Learning 2

Regularization Methods for Large Scale Machine Learning 3

Regularization Methods for Large Scale Machine Learning 4

Exploring the High-dimensional Random Landscapes of Data Science (3/3)

Collective Motions with Congestion (3/3)

Generative AI and Diffusion Models: a Statistical Physics Analysis (2/3)