Fetching the paper…
Reading the bibliography…
The problem of recovering a matrix of low rank from an incomplete and possibly noisy set of linear measurements arises in a number of areas.
Quantum detection and estimation theory
C. W. Helstrom · 1969
Earlier work this paper cites.
On Milman’s inequality and random subspaces which escape through a mesh in ℝ n {\mathbb{R}}^{n}
Y. Gordon · 1988
Earlier work this paper cites.
Topics in matrix analysis
R. Horn and C. Johnson · 1991
Earlier work this paper cites.
Probability in Banach Spaces
M. Ledoux and M. Talagrand · 1991
Earlier work this paper cites.
Matrix analysis
R. Bhatia · 1997
Earlier work this paper cites.
Strong converse for identification via quantum channels
R. Ahlswede and A. Winter · 2002
Earlier work this paper cites.
Matrix rank minimization
M. Fazel · 2002
Earlier work this paper cites.
Learning with kernels: Support vector machines, regularization, optimization, and beyond
B. Schölkopf and A. J. Smola · 2002
Earlier work this paper cites.
Convex Optimization
S. Boyd and L. Vandenberghe · 2004
Earlier work this paper cites.
Condition numbers of Gaussian random matrices
Z. Chen and J. J. Dongarra · 2005
Earlier work this paper cites.
Some estimates of norms of random matrices
R. Latała · 2005
Earlier work this paper cites.
Tight informationally complete quantum measurements
A. Scott · 2006
Earlier work this paper cites.
Quantum t-designs: t-wise independence in the quantum world
A. Ambainis and J. Emerson · 2007
Earlier work this paper cites.
On the uniqueness of nonnegative sparse solutions to underdetermined systems of equations
A. M. Bruckstein, M. Elad, and M. Zibulevsky · 2008
Earlier work this paper cites.
Necessary and sufficient conditions for success of the nuclear norm heuristic for rank minimization
B. Recht, W. Xu, and B. Hassibi · 2008
Earlier work this paper cites.
On sparse reconstruction from fourier and gaussian measurements
M. Rudelson and R. Vershynin · 2008
Earlier work this paper cites.
Painless reconstruction from magnitudes of frame coefficients
R. Balan, B. G. Bodmann, P. G. Casazza, and D. Edidin · 2009
Earlier work this paper cites.
Exact matrix completion via convex optimization
E. J. Candès and B. Recht · 2009
Earlier work this paper cites.
Distinguishability of quantum states under restricted families of measurements with an application to quantum data hiding
W. Matthews, S. Wehner, and A. Winter · 2009
Earlier work this paper cites.
The power of convex relaxation: near-optimal matrix completion
E. Candes and T. Tao · 2010
Earlier work this paper cites.
State tomography via compressed sensing
D. Gross, Y.-K. Liu, S. T. Flammia, S. Becker, and J. Eisert · 2010
Earlier work this paper cites.
ADMiRA: Atomic decomposition for minimum rank approximation
K. Lee and Y. Bresler · 2010
Earlier work this paper cites.
Iterative reweighted least squares for matrix rank minimization
K. Mohan and M. Fazel · 2010
Earlier work this paper cites.
New restricted isometry results for noisy low-rank recovery
K. Mohan and M. Fazel · 2010
Cited alongside, same era.
Quantum computation and quantum information
M. A. Nielsen and I. L. Chuang · 2010
Cited alongside, same era.
Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
B. Recht, M. Fazel, and P. A. Parrilo · 2010
Cited alongside, same era.
Tight oracle inequalities for low-rank matrix recovery from a minimal number of noisy random measurements
E. J. Candès and Y. Plan · 2011
Cited alongside, same era.
Low-rank matrix recovery via iteratively reweighted least squares minimization
M. Fornasier, H. Rauhut, and R. Ward · 2011
Cited alongside, same era.
Universal low-rank matrix recovery from Pauli measurements
Y.-K. Liu · 2011
Low rank matrix recovery from rank one measurements
R. Kueng, H. Rauhut, and U. Terstiege · 2014
Later among the works it cites.
Sharp recovery bounds for convex demixing, with applications
M. B. McCoy and J. A. Tropp · 2014
Later among the works it cites.
Proximal algorithms
N. Parikh and S. Boyd · 2014
Later among the works it cites.
Convex recovery of a structured signal from independent random linear measurements
J. A. Tropp · 2014
Later among the works it cites.
Compressive multiplexing of correlated signals
A. Ahmed and J. Romberg · 2015
Closest in time.
Phase retrieval via Wirtinger flow: Theory and algorithms
E. J. Candès, X. Li, and M. Soltanolkotabi · 2015
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
A simplified approach to recovery conditions for low rank matrices
S. Oymak, K. Mohan, M. Fazel, and B. Hassibi · 2011
Cited alongside, same era.
Null space conditions and thresholds for rank minimization
B. Recht, W. Xu, and B. Hassibi · 2011
Cited alongside, same era.
The convex geometry of linear inverse problems
V. Chandrasekaran, B. Recht, P. Parrilo, and A. Willsky · 2012
Cited alongside, same era.
Quantum tomography via compressed sensing: error bounds, sample complexity and efficient estimators
S. T. Flammia, D. Gross, Y.-K. Liu, and J. Eisert · 2012
Cited alongside, same era.
User-friendly tail bounds for sums of random matrices
J. A. Tropp · 2012
Cited alongside, same era.
Introduction to the non-asymptotic analysis of random matrices
R. Vershynin · 2012
Cited alongside, same era.
Closest in time.
Uncertainty quantification for matrix compressed sensing and quantum tomography problems
A. Carpentier, J. Eisert, D. Gross, and R. Nickl · 2015
Closest in time.
Exact and stable covariance estimation from quadratic sampling via convex programming
Y. Chen, Y. Chi, and A. Goldsmith · 2015
Closest in time.
C. Ferrie and R. Kueng · 2015
Closest in time.
Improved recovery guarantees for phase retrieval from coded diffraction patterns
D. Gross, F. Krahmer, and R. Kueng · 2015
Closest in time.
Analysis of low rank matrix recovery via mendelson’s small ball method
M. Kabanava, H. Rauhut, and U. Terstiege · 2015
Closest in time.
On the minimal number of measurements in low-rank matrix recovery
M. Kabanava, H. Rauhut, and U. Terstiege · 2015
Closest in time.
Informationally complete measurements from compressed sensing methodology
A. Kalev, C. Riofrio, R. Kosut, and I. Deutsch · 2015
Closest in time.
The role of topology in quantum tomography
M. Kech, P. Vrana, and M. Wolf · 2015
Closest in time.
From quantum tomography to phase retrieval and back
M. Kech and M. Wolf · 2015
Closest in time.
Quantum tomography of semi-algebraic sets with constrained measurements
M. Kech and M. M. Wolf · 2015
Closest in time.
Bounding the smallest singular value of a random matrix without concentration
V. Koltchinskii and S. Mendelson · 2015
Closest in time.
Direct characterization of linear-optical networks via PhaseLift
R. Kueng, S. Daniel, and D. Gross · 2015
Closest in time.
Spherical designs as a tool for derandomization: The case of PhaseLift
R. Kueng, D. Gross, and F. Krahmer · 2015
Closest in time.
Learning without Concentration
S. Mendelson · 2015
Closest in time.
Regularization-free estimation in trace regression with symmetric positive semidefinite matrices
M. Slawski, P. Li, and M. Hein · 2015
Closest in time.
The minimal measurement number for low-rank matrices recovery
Z. Xu · 2015
Closest in time.