4 papers
Submatrices with non-uniformly selected random supports and insights into sparse approximation
Simon Ruetz, Karin Schnass
In this paper we derive tail bounds on the norms of random submatrices with non-uniformly distributed supports. We apply these results to sparse approximation and conduct an analys…
Average performance of Orthogonal Matching Pursuit (OMP) for sparse approximation
Karin Schnass
We present a theoretical analysis of the average performance of OMP for sparse approximation. For signals that are generated from a dictionary with atoms and coherence and…
Compressed Dictionary Learning
Karin Schnass, Flavio Teixeira
In this paper we show that the computational complexity of the Iterative Thresholding and K-residual-Means (ITKrM) algorithm for dictionary learning can be significantly reduced by…
Dictionary learning -- from local towards global and adaptive
Marie Christine Pali, Karin Schnass
This paper studies the convergence behaviour of dictionary learning via the Iterative Thresholding and K-residual Means (ITKrM) algorithm. On one hand it is proved that ITKrM is a…