71 citations · 151 across the 8 of their papers we have counts for
9 papers
Parseval Proximal Neural Networks
Marzieh Hasannasab, Johannes Hertrich, Sebastian Neumayer +3
The aim of this paper is twofold. First, we show that a certain concatenation of a proximity operator with an affine operator is again a proximity operator on a suitable Hilbert sp…
Frame Soft Shrinkage as Proximity Operator
Marzieh Hassanasab, Sebastian Neumayer, Gerlind Plonka +3
Let and be real Hilbert spaces and an injective operator with closed range and Moore-Penrose inverse $T^\dagge…
On the Robust PCA and Weiszfeld's Algorithm
Sebastian Neumayer, Max Nimmer, Simon Setzer +1
Principal component analysis (PCA) is a powerful standard tool for reducing the dimensionality of data. Unfortunately, it is sensitive to outliers so that various robust PCA varian…
On the Rotational Invariant -Norm PCA
Sebastian Neumayer, Max Nimmer, Simon Setzer +1
Principal component analysis (PCA) is a powerful tool for dimensionality reduction. Unfortunately, it is sensitive to outliers, so that various robust PCA variants were proposed in…
Optimising Spatial and Tonal Data for PDE-based Inpainting
Laurent Hoeltgen, Markus Mainberger, Sebastian Hoffmann +6
Some recent methods for lossy signal and image compression store only a few selected pixels and fill in the missing structures by inpainting with a partial differential equation (P…
Robust PCA: Optimization of the Robust Reconstruction Error over the Stiefel Manifold
Anastasia Podosinnikova, Simon Setzer, Matthias Hein
It is well known that Principal Component Analysis (PCA) is strongly affected by outliers and a lot of effort has been put into robustification of PCA. In this paper we present a n…