Jan Vybíral

According to our database, Jan Vybíral authored at least 26 papers between 2007 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Algorithms and Complexity for Continuous Problems (Dagstuhl Seminar 23351).

Dmitriy Bilyk, Michael Gnewuch, Jan Vybíral, Larisa Yaroslavtseva, Kumar Harsha

Dagstuhl Reports, 2023

A tight lower bound on the minimal dispersion.

Matej Trödler, Jan Volec, Jan Vybíral

CoRR, 2023

A multivariate Riesz basis of ReLU neural networks.

Cornelia Schneider, Jan Vybíral

CoRR, 2023

New lower bounds for the integration of periodic functions.

David Krieg, Jan Vybíral

CoRR, 2023

2022

Lower bounds for integration and recovery in <i>L</i>₂.

Aicke Hinrichs, David Krieg, Erich Novak, Jan Vybíral

J. Complex., 2022

Deterministic Constructions of High-Dimensional Sets with Small Dispersion.

Mario Ullrich, Jan Vybíral

Algorithmica, 2022

2021

Lower bounds for the error of quadrature formulas for Hilbert spaces.

Aicke Hinrichs, David Krieg, Erich Novak, Jan Vybíral

J. Complex., 2021

Lower bounds for integration and recovery in L₂.

Aicke Hinrichs, David Krieg, Erich Novak, Jan Vybíral

CoRR, 2021

2020

On the volume of unit balls of finite-dimensional Lorentz spaces.

Anna Dolezalová, Jan Vybíral

J. Approx. Theory, 2020

2019

The minimal k-dispersion of point sets in high dimensions.

Aicke Hinrichs, Joscha Prochno, Mario Ullrich, Jan Vybíral

J. Complex., 2019

A variant of Schur's product theorem and its applications.

Jan Vybíral

CoRR, 2019

2018

An upper bound on the minimal dispersion.

Mario Ullrich, Jan Vybíral

J. Complex., 2018

Identification of Shallow Neural Networks by Fewest Samples.

Massimo Fornasier, Jan Vybíral, Ingrid Daubechies

CoRR, 2018

2017

Non-Asymptotic Analysis of ℓ₁-Norm Support Vector Machines.

Anton Kolleck, Jan Vybíral

IEEE Trans. Inf. Theory, 2017

Sparse Proteomics Analysis - a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data.

Tim O. F. Conrad, Martin Genzel, Nada Cvetkovic, Niklas Wulkow, Alexander B. Leichtle, Jan Vybíral, Gitta Kutyniok, Christof Schütte

BMC Bioinform., 2017

2015

On some aspects of approximation of ridge functions.

Anton Kolleck, Jan Vybíral

J. Approx. Theory, 2015

2014

Weak and quasi-polynomial tractability of approximation of infinitely differentiable functions.

Jan Vybíral

J. Complex., 2014

2012

Learning Functions of Few Arbitrary Linear Parameters in High Dimensions.

Massimo Fornasier, Karin Schnass, Jan Vybíral

Found. Comput. Math., 2012

2011

Johnson-Lindenstrauss lemma for circulant matrices.

Aicke Hinrichs, Jan Vybíral

Random Struct. Algorithms, 2011

Particle Systems and Kinetic Equations Modeling Interacting Agents in High Dimension.

Massimo Fornasier, Jan Haskovec, Jan Vybíral

Multiscale Model. Simul., 2011

On positive positive-definite functions and Bochner's Theorem.

Aicke Hinrichs, Jan Vybíral

J. Complex., 2011

Compressed learning of high-dimensional sparse functions.

Karin Schnass, Jan Vybíral

Proceedings of the IEEE International Conference on Acoustics, 2011

2009

Corrigendum to the paper: "On approximation numbers of Sobolev embeddings of weighted function spaces" [J. Approx. Theory 136 (2005) 91-107].

Leszek Skrzypczak, Jan Vybíral

J. Approx. Theory, 2009

2008

Widths of embeddings in function spaces.

Jan Vybíral

J. Complex., 2008

Linear information versus function evaluations for L₂-approximation.

Aicke Hinrichs, Erich Novak, Jan Vybíral

J. Approx. Theory, 2008

2007

Sampling numbers and function spaces.

Jan Vybíral

J. Complex., 2007