2.9k citations · 18.4k across the 101 of their papers we have counts for
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cs.IT2015★ 15 cited
Improving compressed sensing with the diamond norm
Martin Kliesch, Richard Kueng, Jens Eisert +1
In low-rank matrix recovery, one aims to reconstruct a low-rank matrix from a minimal number of linear measurements. Within the paradigm of compressed sensing, this is made computa…
math.ST2015★ 21 cited
Uncertainty Quantification for Matrix Compressed Sensing and Quantum Tomography Problems
Alexandra Carpentier, Jens Eisert, David Gross +1
We construct minimax optimal non-asymptotic confidence sets for low rank matrix recovery algorithms such as the Matrix Lasso or Dantzig selector. These are employed to devise adapt…