Publications associées à Logarithmically concave function

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Non-local Functionals Related to the Total Variation and Connections with Image Processing

Hoài-Minh Nguyên

We present new results concerning the approximation of the total variation,

\int_{\Omega} |\nabla u|

, of a function

u

by non-local, non-convex functionals of the form $$ \Lambda_\delta u = \int_{\Omega} \int_{\Omega} \frac{\delta \varphi \big( |u(x) - ...

2018

Logarithmically concave function

Graph Chatbot

Chattez avec Graph Search

Gamma-Blind Fast Neutron Detection for Spent Nuclear Fuel Characterization

Surface roughness and shear resistance in cracked concrete

Double-Loop Unadjusted Langevin Algorithm

Direct FEM-Domain Decomposition Using Convex-to-Concave Spherical Ports for Space Applications

On Separable Quadratic Lyapunov Functions for Convex Design of Distributed Controllers

Sampling can be faster than optimization

Dimension-free Information Concentration via Exp-Concavity

Non-local Functionals Related to the Total Variation and Connections with Image Processing

High-dimensional peaks-over-threshold inference

Non-convex, non-local functionals converging to the total variation

Gamma-Blind Fast Neutron Detection for Spent Nuclear Fuel Characterization

Surface roughness and shear resistance in cracked concrete

Direct FEM-Domain Decomposition Using Convex-to-Concave Spherical Ports for Space Applications

High-dimensional peaks-over-threshold inference

On Separable Quadratic Lyapunov Functions for Convex Design of Distributed Controllers

Sampling can be faster than optimization

Dimension-free Information Concentration via Exp-Concavity

Non-convex, non-local functionals converging to the total variation

Non-local Functionals Related to the Total Variation and Connections with Image Processing

Double-Loop Unadjusted Langevin Algorithm