45 citations · 144 across the 25 of their papers we have counts for
29 papers
Three-dimensional blind deconvolution by CP-parameterized kernels
Fatoumata Sanogo, Stefan Kindermann
We consider the problem of reconstructing a kernel and image in a blind deconvolution problem from convolutional data . We particularly focus on the 3D case, i.e.,…
Adaptive learning of density ratios in RKHS
Werner Zellinger, Stefan Kindermann, Sergei V. Pereverzyev
Estimating the ratio of two probability densities from finitely many observations of the densities is a central problem in machine learning and statistics with applications in two-…
A rational conjugate gradient method for linear ill-conditioned problems
Stefan Kindermann, Werner Zellinger
We consider linear ill-conditioned operator equations in a Hilbert space setting. Motivated by the aggregation method, we consider approximate solutions constructed from linear com…
Multiscale hierarchical decomposition methods for ill-posed problems
Stefan Kindermann, Elena Resmerita, Tobias Wolf
The Multiscale Hierarchical Decomposition Method (MHDM) was introduced as an iterative method for total variation regularization, with the aim of recovering details at various scal…
A numerical comparison of some heuristic stopping rules for nonlinear Landweber iteration
Simon Hubmer, Ekaterina Sherina, Stefan Kindermann +1
The choice of a suitable regularization parameter is an important part of most regularization methods for inverse problems. In the absence of reliable estimates of the noise level,…
Tensor Deblurring and Denoising Using Total Variation
Fatoumata Sanogo, Carmeliza Navasca, Stefan Kindermann
We consider denoising and deblurring problems for tensors. While images can be discretized as matrices, the analogous procedure for color images or videos leads to a tensor formula…