Fetching the paper…
Reading the bibliography…
This paper studies noisy low-rank matrix completion: given partial and noisy entries of a large low-rank matrix, the goal is to estimate the underlying matrix faithfully and efficiently.
A note on the use of principal components in regression
I. T. Jolliffe · 1982
Earlier work this paper cites.
Shape and motion from image streams under orthography: a factorization method
C. Tomasi and T. Kanade · 1992
Earlier work this paper cites.
Real and functional analysis
S. Lang · 1993
Earlier work this paper cites.
Problems of distance geometry and convex properties of quadratic maps
A. I. Barvinok · 1995
Earlier work this paper cites.
Matrix rank minimization with applications
M. Fazel · 2002
Earlier work this paper cites.
A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization
S. Burer and R. D. Monteiro · 2003
Earlier work this paper cites.
Log-det heuristic for matrix rank minimization with applications to Hankel and Euclidean distance matrices
M. Fazel, H. Hindi, and S. P. Boyd · 2003
Earlier work this paper cites.
Rank minimization and applications in system theory
M. Fazel, H. Hindi, and S. Boyd · 2004
Earlier work this paper cites.
Fast maximum margin matrix factorization for collaborative prediction
J. D. Rennie and N. Srebro · 2005
Earlier work this paper cites.
Rank, trace-norm and max-norm
N. Srebro and A. Shraibman · 2005
Earlier work this paper cites.
Confidence intervals for diffusion index forecasts and inference for factor-augmented regressions
J. Bai and S. Ng · 2006
Earlier work this paper cites.
Correlation and large-scale simultaneous significance testing
B. Efron · 2007
Earlier work this paper cites.
Theory of semidefinite programming for sensor network localization
A. M.-C. So and Y. Ye · 2007
Earlier work this paper cites.
“Preconditioning” for feature selection and regression in high-dimensional problems
D. Paul, E. Bair, T. Hastie, and R. Tibshirani · 2008
Earlier work this paper cites.
A fast iterative shrinkage-thresholding algorithm for linear inverse problems
A. Beck and M. Teboulle · 2009
Earlier work this paper cites.
Exact matrix completion via convex optimization
E. Candès and B. Recht · 2009
Earlier work this paper cites.
Interior-point method for nuclear norm approximation with application to system identification
Z. Liu and L. Vandenberghe · 2009
Earlier work this paper cites.
A singular value thresholding algorithm for matrix completion
J. F. Cai, E. J. Candès, and Z. Shen · 2010
Earlier work this paper cites.
Matrix completion with noise
E. Candès and Y. Plan · 2010
Earlier work this paper cites.
The power of convex relaxation: Near-optimal matrix completion
E. Candès and T. Tao · 2010
Earlier work this paper cites.
Correlated z-values and the accuracy of large-scale statistical estimates
B. Efron · 2010
Earlier work this paper cites.
Guaranteed rank minimization via singular value projection
P. Jain, R. Meka, and I. S. Dhillon · 2010
Earlier work this paper cites.
Matrix completion from a few entries
R. H. Keshavan, A. Montanari, and S. Oh · 2010
Earlier work this paper cites.
Matrix completion from noisy entries
R. H. Keshavan, A. Montanari, and S. Oh · 2010
Earlier work this paper cites.
Spectral regularization algorithms for learning large incomplete matrices
R. Mazumder, T. Hastie, and R. Tibshirani · 2010
Earlier work this paper cites.
Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
B. Recht, M. Fazel, and P. A. Parrilo · 2010
Earlier work this paper cites.
An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems
K.-C. Toh and S. Yun · 2010
Earlier work this paper cites.
Stable principal component pursuit
Z. Zhou, X. Li, J. Wright, E. Candès, and Y. Ma · 2010
Earlier work this paper cites.
Robust principal component analysis?
E. Candès, X. Li, Y. Ma, and J. Wright · 2011
Earlier work this paper cites.
Rank-sparsity incoherence for matrix decomposition
V. Chandrasekaran, S. Sanghavi, P. A. Parrilo, and A. S. Willsky · 2011
Earlier work this paper cites.
Low-rank matrix recovery via iteratively reweighted least squares minimization
M. Fornasier, H. Rauhut, and R. Ward · 2011
Earlier work this paper cites.
Recovering low-rank matrices from few coefficients in any basis
D. Gross · 2011
Earlier work this paper cites.
Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion
V. Koltchinskii, K. Lounici, and A. B. Tsybakov · 2011
Earlier work this paper cites.
Factor models and variable selection in high-dimensional regression analysis
A. Kneip and P. Sarda · 2011
Earlier work this paper cites.
Fixed point and bregman iterative methods for matrix rank minimization
S. Ma, D. Goldfarb, and L. Chen · 2011
Earlier work this paper cites.
A simpler approach to matrix completion
B. Recht · 2011
Cited alongside, same era.
Estimation of high-dimensional low-rank matrices
A. Rohde, A. B. Tsybakov, et al · 2011
Cited alongside, same era.
Angular synchronization by eigenvectors and semidefinite programming
A. Singer · 2011
Cited alongside, same era.
Estimating false discovery proportion under arbitrary covariance dependence
J. Fan, X. Han, and W. Gu · 2012
Cited alongside, same era.
How to make the gradients small
Y. Nesterov · 2012
Cited alongside, same era.
Restricted strong convexity and weighted matrix completion: Optimal bounds with noise
S. Negahban and M. Wainwright · 2012
Cited alongside, same era.
Guaranteed matrix completion via non-convex factorization
R. Sun and Z.-Q. Luo · 2016
Later among the works it cites.
Low-rank solutions of linear matrix equations via procrustes flow
S. Tu, R. Boczar, M. Simchowitz, M. Soltanolkotabi, and B. Recht · 2016
Later among the works it cites.
Guarantees of riemannian optimization for low rank matrix recovery
K. Wei, J.-F. Cai, T. Chan, and S. Leung · 2016
Later among the works it cites.
A unified computational and statistical framework for nonconvex low-rank matrix estimation
L. Wang, X. Zhang, and Q. Gu · 2016
Later among the works it cites.
Fast algorithms for robust PCA via gradient descent
X. Yi, D. Park, Y. Chen, and C. Caramanis · 2016
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Introduction to the non-asymptotic analysis of random matrices
R. Vershynin · 2012
Cited alongside, same era.
Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm
Z. Wen, W. Yin, and Y. Zhang · 2012
Cited alongside, same era.
Low-rank matrix recovery from errors and erasures
Y. Chen, A. Jalali, S. Sanghavi, and C. Caramanis · 2013
Cited alongside, same era.
Large covariance estimation by thresholding principal orthogonal complements
J. Fan, Y. Liao, and M. Mincheva · 2013
Cited alongside, same era.
Noisy matrix completion using alternating minimization
S. Gunasekar, A. Acharya, N. Gaur, and J. Ghosh · 2013
Cited alongside, same era.
Consistent shape maps via semidefinite programming
Q.-X. Huang and L. Guibas · 2013
Cited alongside, same era.
Q. Zheng and J. Lafferty · 2016
Later among the works it cites.
Entrywise eigenvector analysis of random matrices with low expected rank
E. Abbe, J. Fan, K. Wang, and Y. Zhong · 2017
Later among the works it cites.
Solving random quadratic systems of equations is nearly as easy as solving linear systems
Y. Chen and E. J. Candès · 2017
Later among the works it cites.
J. Chen and X. Li · 2017
Later among the works it cites.
Sufficient forecasting using factor models
J. Fan, L. Xue, and J. Yao · 2017
Later among the works it cites.
No spurious local minima in nonconvex low rank problems: A unified geometric analysis
R. Ge, C. Jin, and Y. Zheng · 2017
Later among the works it cites.
Blind demixing and deconvolution at near-optimal rate
P. Jung, F. Krahmer, and D. Stöger · 2017
Later among the works it cites.
Blind deconvolution meets blind demixing: Algorithms and performance bounds
S. Ling and T. Strohmer · 2017
Later among the works it cites.
C. Ma, K. Wang, Y. Chi, and Y. Chen · 2017
Later among the works it cites.
Non-square matrix sensing without spurious local minima via the burer-monteiro approach
D. Park, A. Kyrillidis, C. Carmanis, and S. Sanghavi · 2017
Later among the works it cites.
P. Sur, Y. Chen, and E. J. Candès · 2017
Later among the works it cites.
A nonconvex approach for phase retrieval: Reshaped wirtinger flow and incremental algorithms
H. Zhang, Y. Zhou, Y. Liang, and Y. Chi · 2017
Later among the works it cites.
The projected power method: An efficient algorithm for joint alignment from pairwise differences
Y. Chen and E. Candès · 2018
Later among the works it cites.
Harnessing structures in big data via guaranteed low-rank matrix estimation: Recent theory and fast algorithms via convex and nonconvex optimization
Y. Chen and Y. Chi · 2018
Later among the works it cites.
Asymmetry helps: Eigenvalue and eigenvector analyses of asymmetrically perturbed low-rank matrices
Y. Chen, C. Cheng, and J. Fan · 2018
Later among the works it cites.
The leave-one-out approach for matrix completion: Primal and dual analysis
L. Ding and Y. Chen · 2018
Later among the works it cites.
Factor-adjusted regularized model selection
J. Fan, Y. Ke, and K. Wang · 2018
Later among the works it cites.
Nonconvex matrix factorization from rank-one measurements
Y. Li, C. Ma, Y. Chen, and Y. Chi · 2018
Later among the works it cites.
Approximate support recovery of atomic line spectral estimation: A tale of resolution and precision
Q. Li and G. Tang · 2018
Later among the works it cites.
Near-optimal bound for phase synchronization
Y. Zhong and N. Boumal · 2018
Later among the works it cites.
Gradient descent with random initialization: Fast global convergence for nonconvex phase retrieval
Y. Chen, Y. Chi, J. Fan, and C. Ma · 2019
Closest in time.
Spectral method and regularized MLE are both optimal for top- K K ranking
Y. Chen, J. Fan, C. Ma, and K. Wang · 2019
Closest in time.
Inference and uncertainty quantification for noisy matrix completion
Y. Chen, J. Fan, C. Ma, and Y. Yan · 2019
Closest in time.
Nonconvex optimization meets low-rank matrix factorization: An overview
Y. Chi, Y. M. Lu, and Y. Chen · 2019
Closest in time.
J. Chen, D. Liu, and X. Li · 2019
Closest in time.
Fast and provable algorithms for spectrally sparse signal reconstruction via low-rank hankel matrix completion
J.-F. Cai, T. Wang, and K. Wei · 2019
Closest in time.
Farmtest: Factor-adjusted robust multiple testing with approximate false discovery control
J. Fan, Y. Ke, Q. Sun, and W.-X. Zhou · 2019
Closest in time.
Robust covariance estimation for approximate factor models
J. Fan, W. Wang, and Y. Zhong · 2019
Closest in time.
Matrix completion with deterministic pattern: A geometric perspective
A. Shapiro, Y. Xie, and R. Zhang · 2019
Closest in time.