4 citations · 4 across the 1 of their papers we have counts for
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Relaxations for Non-Separable Cardinality/Rank Penalties
Carl Olsson, Daniele Gerosa, Marcus Carlsson
Rank and cardinality penalties are hard to handle in optimization frameworks due to non-convexity and discontinuity. Strong approximations have been a subject of intense study and…
On phase retrieval via matrix completion and the estimation of low rank PSD matrices
Marcus Carlsson, Daniele Gerosa
Given underdetermined measurements of a Positive Semi-Definite (PSD) matrix of known low rank , we present a new algorithm to estimate based on recent advances in non-co…
Bias Reduction in Compressed Sensing
Carl Olsson, Marcus Carlsson, Daniele Gerosa
Sparsity and rank functions are important ways of regularizing under-determined linear systems. Optimization of the resulting formulations is made difficult since both these penalt…
An unbiased approach to compressed sensing
Marcus Carlsson, Daniele Gerosa, Carl Olsson
In compressed sensing a sparse vector is approximately retrieved from an under-determined equation system . Exact retrieval would mean solving a large combinatorial problem w…