Peter Mathé

J. Complex., 2024

Comparing the ill-posedness for linear operators in Hilbert spaces.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Inverse learning in Hilbert scales.

[BibT_eX]

[DOI]

Abhishake Rastogi

Mach. Learn., July, 2023

2022

Stochastic gradient descent for linear inverse problems in Hilbert spaces.

[BibT_eX]

[DOI]

Math. Comput., 2022

2021

The degree of ill-posedness of composite linear ill-posed problems with focus on the impact of the non-compact Hausdorff moment operator.

[BibT_eX]

[DOI]

CoRR, 2021

2020

Nonlinear Tikhonov regularization in Hilbert scales with oversmoothing penalty: inspecting balancing principles.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Bayesian inverse problems with non-commuting operators.

[BibT_eX]

[DOI]

Math. Comput., 2019

2018

Optimal rates for Lavrentiev regularization with adjoint source conditions.

[BibT_eX]

[DOI]

Robert Plato

Math. Comput., 2018

Analysis of regularized Nyström subsampling for regression functions of low smoothness.

[BibT_eX]

[DOI]

Sergiy Pereverzyev Jr.

CoRR, 2018

Minimax Rates for Statistical Inverse Problems Under General Source Conditions.

[BibT_eX]

[DOI]

Litao Ding

Comput. Methods Appl. Math., 2018

2017

Complexity of linear ill-posed problems in Hilbert space.

[BibT_eX]

[DOI]

J. Complex., 2017

2014

Discrepancy based model selection in statistical inverse problems.

[BibT_eX]

[DOI]

J. Complex., 2014

2013

Heuristic parameter selection based on functional minimization: Optimality and model function approach.

[BibT_eX]

[DOI]

Math. Comput., 2013

Oracle Inequality for a Statistical Raus-Gfrerer-Type Rule.

[BibT_eX]

[DOI]

Qinian Jin

SIAM/ASA J. Uncertain. Quantification, 2013

2011

Parameter choice methods using minimization schemes.

[BibT_eX]

[DOI]

Frank Bauer

J. Complex., 2011

2009

The use of higher order finite difference schemes is not dangerous.

[BibT_eX]

[DOI]

J. Complex., 2009

2008

Direct and inverse results in variable Hilbert scales.

[BibT_eX]

[DOI]

J. Approx. Theory, 2008

2007

Analysis of Profile Functions for General Linear Regularization Methods.

[BibT_eX]

[DOI]

SIAM J. Numer. Anal., 2007

Simple Monte Carlo and the Metropolis algorithm.

[BibT_eX]

[DOI]

Erich Novak

J. Complex., 2007

2006

Regularization of some linear ill-posed problems with discretized random noisy data.

[BibT_eX]

[DOI]

Math. Comput., 2006

The discretized discrepancy principle under general source conditions.

[BibT_eX]

[DOI]

J. Complex., 2006

2004

Saturation of Regularization Methods for Linear Ill-Posed Problems in Hilbert Spaces.

[BibT_eX]

[DOI]

SIAM J. Numer. Anal., 2004

Quasi-Monte Carlo integration over Reald.

[BibT_eX]

[DOI]

Gang Wei

Math. Comput., 2004

2002

Direct Estimation of Linear Functionals from Indirect Noisy Observations.

[BibT_eX]

[DOI]

J. Complex., 2002

2002 Best Paper Award Committee.

[BibT_eX]

[DOI]

Fred J. Hickernell

J. Complex., 2002

Stable Summation of Orthogonal Series with Noisy Coefficients.

[BibT_eX]

[DOI]

J. Approx. Theory, 2002

2001

Optimal Discretization of Inverse Problems in Hilbert Scales. Regularization and Self-Regularization of Projection Methods.

[BibT_eX]

[DOI]

SIAM J. Numer. Anal., 2001

1999

Numerical Integration using Markov Chains.

[BibT_eX]

[DOI]

Monte Carlo Methods Appl., 1999

1998

Relaxation of Product Markov Chains on Product Spaces.

[BibT_eX]

[DOI]

J. Complex., 1998

Asymptotically Optimal Weighted Numerical Integration.

[BibT_eX]

[DOI]

J. Complex., 1998

1997

On quasi-Monte Carlo simulation of stochastic differential equations.

[BibT_eX]

[DOI]

Norbert Hofmann

Math. Comput., 1997

1995

The Optimal Error of Monte Carlo Integration.

[BibT_eX]

[DOI]

J. Complex., 1995

1993

On Optimal Random Nets.

[BibT_eX]

[DOI]

J. Complex., 1993

1991

Random approximation of Sobolev embeddings.

[BibT_eX]

[DOI]

J. Complex., 1991

1990

s-Numbers in information-based complexity.

[BibT_eX]

[DOI]