11 citations · 16 across the 5 of their papers we have counts for
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Sparse recovery in bounded Riesz systems with applications to numerical methods for PDEs
Simone Brugiapaglia, Sjoerd Dirksen, Hans Christian Jung +1
We study sparse recovery with structured random measurement matrices having independent, identically distributed, and uniformly bounded rows and with a nontrivial covariance struct…
Robust one-bit compressed sensing with partial circulant matrices
Sjoerd Dirksen, Shahar Mendelson
We present optimal sample complexity estimates for one-bit compressed sensing problems in a realistic scenario: the procedure uses a structured matrix (a randomly sub-sampled circu…
Non-Gaussian Hyperplane Tessellations and Robust One-Bit Compressed Sensing
Sjoerd Dirksen, Shahar Mendelson
We show that a tessellation generated by a small number of random affine hyperplanes can be used to approximate Euclidean distances between any two points in an arbitrary bounded s…
One-bit compressed sensing with partial Gaussian circulant matrices
Sjoerd Dirksen, Hans Christian Jung, Holger Rauhut
In this paper we consider memoryless one-bit compressed sensing with randomly subsampled Gaussian circulant matrices. We show that in a small sparsity regime and for small enough a…
On the gap between RIP-properties and sparse recovery conditions
Sjoerd Dirksen, Guillaume Lecué, Holger Rauhut
We consider the problem of recovering sparse vectors from underdetermined linear measurements via -constrained basis pursuit. Previous analyses of this problem based on gen…