Hochschulschrift
Multivariate Approximation and High-Dimensional Sparse FFT Based on Rank-1 Lattice Sampling
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
Chemnitz, Technische Universität Chemnitz, Dissertation, 2017
- Keyword
-
Multivariate Approximation
Schnelle Fourier-Transformation
Multivariate Approximation
Schnelle Fourier-Transformation
Diskrete Fourier-Transformation
DCT
- Event
-
Veröffentlichung
- (where)
-
Chemnitz, Chemnitz
- (who)
-
Universitätsbibliothek Chemnitz, Universitätsverlag der Technischen Universität Chemnitz
- (when)
-
2017
- Creator
- Contributor
-
Potts, Daniel
Potts, Daniel
Plonka-Hoch, Gerlind
Pflüger, Dirk
- URN
-
urn:nbn:de:bsz:ch1-qucosa-222820
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
25.03.2025, 1:43 PM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Hochschulschrift
Associated
- Volkmer, Toni
- Potts, Daniel
- Plonka-Hoch, Gerlind
- Pflüger, Dirk
- Universitätsbibliothek Chemnitz, Universitätsverlag der Technischen Universität Chemnitz
Time of origin
- 2017
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Inference for high-dimensional sparse econometric models
Sparse High-dimensional Approximation from Highly Noisy Data
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Practical lattice basis sampling reduction
L1-Penalised quantile regression in high-dimensional sparse models
Sparse and robust classification methods for high-dimensional datasets
Efficient high-dimensional importance sampling in mixture frameworks
High-dimensional sparse financial networks through a regularised regression model
Multivariate Approximation and high-dimensional sparse FFT based on rank-1 lattice sampling
Deterministic Sparse FFT Algorithms
Sampling inequalities for sparse grids
Sparse sampling for scatterer localisation
Inference for high-dimensional sparse econometric models
Sparse High-dimensional Approximation from Highly Noisy Data
Spatially adaptive sparse grids for high-dimensional problems
Practical lattice basis sampling reduction
L1-Penalised quantile regression in high-dimensional sparse models
Sparse and robust classification methods for high-dimensional datasets
Efficient high-dimensional importance sampling in mixture frameworks