4 papers
Convergence of alternating minimisation algorithms for dictionary learning
Simon Ruetz, Karin Schnass
In this paper we derive sufficient conditions for the convergence of two popular alternating minimisation algorithms for dictionary learning - the Method of Optimal Directions (MOD…
Bounds for matrices of inclusion probabilities in rejective sampling
Simon Ruetz, Karin Schnass
Motivated by a desire to model n-sparse signals more realistically, we study matrices of inclusion probabilities for conditional Poisson or rejective sampling in the non-asymptotic…
Adapted variable density subsampling for compressed sensing
Simon Ruetz
Recent results in compressed sensing showed that the optimal subsampling strategy should take into account the sparsity pattern of the signal at hand. This oracle-like knowledge, e…
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…