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The matrix rank minimization problem has applications in many fields such as system identification, optimal control, low-dimensional embedding, etc.
A singular value thresholding algorithm for matrix completion
Cai, J., Candès, E. J., and Shen, Z · 1982
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Rank minimization under LMI constraints: A framework for output feedback problems
Ghaoui, L. E., and Gahinet, P · 1993
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Convex Analysis and Minimization Algorithms II: Advanced Theory and Bundle Methods
Hiriart-Urruty, J.-B., and Lemaréchal, C · 1993
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The geometry of graphs and some of its algorithmic applications
Linial, N., London, E., and Rabinovich, Y · 1995
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Sparse approximate solutions to linear systems
Natarajan, B. K · 1995
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Regression shrinkage and selection via the lasso
Tibshirani, R · 1996
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Mathematical Control theory
Sontag, E · 1998
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SDPT3 - a Matlab software package for semidefinite programming
Toh, K.-C., Todd, M. J., and Tütüncü, R. H · 1999
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A rank minimization heuristic with application to minimum order system approximation
Fazel, M., Hindi, H., and Boyd, S · 2001
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Convex Analysis and Nonlinear Optimization
Borwein, J. M., and Lewis, A. S · 2003
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Log-det heuristic for matrix rank minimization with applications to Hankel and Euclidean distance matrices
Fazel, M., Hindi, H., and Boyd, S · 2003
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Weighted low-rank approximations
Srebro, N., and Jaakkola, T · 2003
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Rank minimization and applications in system theory
Fazel, M., Hindi, H., and Boyd, S · 2004
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Learning with Matrix Factorizations
Srebro, N · 2004
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ℓ 1 \ell_{1} -MAGIC: Recovery of sparse signals via convex programming
Candès, E. J., and Romberg, J · 2005
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Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
Candès, E. J., Romberg, J., and Tao, T · 2006
Cited alongside, same era.
Compressed sensing
Donoho, D · 2006
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Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit
Donoho, D., Tsaig, Y., Drori, I., and Starck, J.-C · 2006
Cited alongside, same era.
Fast Monte Carlo algorithms for matrices ii: Computing low-rank approximations to a matrix
Drineas, P., Kannan, R., and Mahoney, M. W · 2006
Cited alongside, same era.
Just relax: Convex programming methods for identifying sparse signals
Tropp, J · 2006
Cited alongside, same era.
Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems
Subspace pursuit for compressive sensing signal reconstruction
Dai, W., and Milenkovic, O · 2009
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Matrix completion from noisy entries
Keshavan, R. H., Montanari, A., and Oh, S · 2009
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ADMIRA: atomic decomposition for minimum rank approximation
Lee, K., and Bresler, Y · 2009
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Efficient and guaranteed rank minimization by atomic decomposition
Lee, K., and Bresler, Y · 2009
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Lee, K., and Bresler, Y · 2009
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Figueiredo, M. A. T., Nowak, R. D., and Wright, S. J · 2007
Cited alongside, same era.
A method for large-scale ℓ 1 \ell_{1} -regularized least-squares
Kim, S. J., Koh, K., Lustig, M., Boyd, S., and Gorinevsky, D · 2007
Cited alongside, same era.
Gradient pursuits
Blumensath, T., and Davies, M. E · 2008
Cited alongside, same era.
Fast solution of ℓ 1 \ell_{1} -norm minimization problems when the solution may be sparse
Donoho, D. L., and Tsaig, Y · 2008
Cited alongside, same era.
Fixed-point continuation for ℓ 1 \ell_{1} -minimization: Methodology and convergence
Hale, E. T., Yin, W., and Zhang, Y · 2008
Cited alongside, same era.
Probing the Pareto frontier for basis pursuit solutions
van den Berg, E., and Friedlander, M. P · 2008
Cited alongside, same era.
Bregman iterative algorithms for ℓ 1 \ell_{1} -minimization with applications to compressed sensing
Yin, W., Osher, S., Goldfarb, D., and Darbon, J · 2008
Cited alongside, same era.
An implementable proximal point algorithmic framework for nuclear norm minimization
Liu, Y., Sun, D., and Toh, K.-C · 2009
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Interior-point method for nuclear norm approximation with application to system identification
Liu, Z., and Vandenberghe, L · 2009
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Fixed point and Bregman iterative methods for matrix rank minimization
Ma, S., Goldfarb, D., and Chen, L · 2009
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Guaranteed rank minimization via singular value projection
Meka, R., Jain, P., and Dhillon, I. S · 2009
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CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
Needell, D., and Tropp, J. A · 2009
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Matrix completion from a few entries
Keshavan, R. H., Montanari, A., and Oh, S · 2010
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Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
Recht, B., Fazel, M., and Parrilo, P · 2010
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An accelerated proximal gradient algorithm for nuclear norm regularized least squares problems
Toh, K.-C., and Yun, S · 2010
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The power of convex relaxation: near-optimal matrix completion
Candès, E. J., and Tao, T · 2080
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