- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Facets of High-Dimensional Gaussian Polytopes ; volume:34 ; number:3 ; day:9 ; month:1 ; year:2024 ; pages:1-16 ; date:3.2024
The journal of geometric analysis ; 34, Heft 3 (9.1.2024), 1-16, 3.2024
- Urheber
-
Böröczky, Károly J.
Lugosi, Gábor
Reitzner, Matthias
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s12220-023-01440-5
- URN
-
urn:nbn:de:101:1-2405020850145.577143197647
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:47 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Böröczky, Károly J.
- Lugosi, Gábor
- Reitzner, Matthias
- SpringerLink (Online service)
Ähnliche Objekte (12)
High-dimensional asymptotics for random polytopes
Facets of spherical random polytopes
Facets of spherical random polytopes
Uniform inference in high-dimensional gaussian graphical models
Counting Vertices of Integral Polytopes Defined by Facets
High-dimensional Bayesian optimization with projections using quantile Gaussian processes
In search of non-Gaussian components of a high-dimensional distribution
Lasso regularization for left-censored Gaussian outcome and high-dimensional predictors
Variational inference and sparsity in high-dimensional deep Gaussian mixture models
In Search of Non-Gaussian Components of a High-Dimensional Distribution
Tiling and PCA Strategy for Clustering-Based High-Dimensional Gaussian Filtering
Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data
High-dimensional asymptotics for random polytopes
Facets of spherical random polytopes
Facets of spherical random polytopes
Uniform inference in high-dimensional gaussian graphical models
Counting Vertices of Integral Polytopes Defined by Facets
High-dimensional Bayesian optimization with projections using quantile Gaussian processes
In search of non-Gaussian components of a high-dimensional distribution
Lasso regularization for left-censored Gaussian outcome and high-dimensional predictors
Variational inference and sparsity in high-dimensional deep Gaussian mixture models
In Search of Non-Gaussian Components of a High-Dimensional Distribution
Tiling and PCA Strategy for Clustering-Based High-Dimensional Gaussian Filtering
Gradient-Based Training of Gaussian Mixture Models for High-Dimensional Streaming Data
High-dimensional asymptotics for random polytopes
Facets of spherical random polytopes
Facets of spherical random polytopes
Uniform inference in high-dimensional gaussian graphical models
Counting Vertices of Integral Polytopes Defined by Facets
High-dimensional Bayesian optimization with projections using quantile Gaussian processes
In search of non-Gaussian components of a high-dimensional distribution
Lasso regularization for left-censored Gaussian outcome and high-dimensional predictors
Variational inference and sparsity in high-dimensional deep Gaussian mixture models
In Search of Non-Gaussian Components of a High-Dimensional Distribution
Tiling and PCA Strategy for Clustering-Based High-Dimensional Gaussian Filtering