15 citations · 26 across the 13 of their papers we have counts for
3 papers · 1 filter
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…
Bilinear Parameterization For Differentiable Rank-Regularization
Marcus Valtonen Örnhag, Carl Olsson, Anders Heyden
Low rank approximation is a commonly occurring problem in many computer vision and machine learning applications. There are two common ways of optimizing the resulting models. Eith…
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…