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Estimation of low-rank matrices is of significant interest in a range of contemporary applications.
Andrews, H. C.H. C. andPatterson, C. L.C. L. III (1976). Singular value decomposition (SVD) image coding. IEEE Trans. Commun. 24 425–432
1976
Earlier work this paper cites.
1985
Earlier work this paper cites.
Laurent, B.B. andMassart, P.P. (2000). Adaptive estimation of a quadratic functional by model selection. Ann. Statist. 28 1302–1338
2000
Earlier work this paper cites.
Trosset, Michael W.M. W. (2000). Distance matrix completion by numerical optimization. Comput. Optim. Appl. 17 11–22
2000
Earlier work this paper cites.
Johnstone, Iain M.I. M. (2001). On the distribution of the largest eigenvalue in principal components analysis. Ann. Statist. 29 295–327
2001
Earlier work this paper cites.
Basri, R.R. andJacobs, D. W.D. W. (2003). Lambertian reflectance and linear sub-spaces. IEEE Trans. Pattern Anal. Mach. Intell. 25 218–233
2003
Earlier work this paper cites.
Patterson, NickN., Price, Alkes L.A. L. andReich, DavidD. (2006). Population structure and eigenanalysis. PLoS Genet. 2 e190
2006
Earlier work this paper cites.
Price, Alkes L.A. L., Patterson, Nick J.N. J., Plenge, Robert M.R. M., Weinblatt, Michael E.M. E., Shadick, Nancy A.N. A. andReich, DavidD. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38 904–909
2006
Earlier work this paper cites.
Wakin, M.M., Laska, J.J., Duarte, M.M., Baron, D.D., Sarvotham, S.S., Takhar, D.D., Kelly, K.K. andBaraniuk, R.R. (2006). An architecture for compressive imaging. In Proceedings of the International Conference on Image Processing (ICIP 2006) 1273–1276
2006
Earlier work this paper cites.
Fan, JianqingJ., Fan, YingyingY. andLv, JinchiJ. (2008). High dimensional covariance matrix estimation using a factor model. J. Econometrics 147 186–197
2008
Earlier work this paper cites.
Grant, Michael C.M. C. andBoyd, Stephen P.S. P. (2008). Graph implementations for nonsmooth convex programs. In Recent Advances in Learning and Control (a tribute to M. Vidyasagar) (V.V. Blondel et al., eds.). Lecture Notes in Control and Inform. Sci. 371 95–110. Springer, London
2008
Earlier work this paper cites.
Cai, T. TonyT. T., Xu, GuangwuG. andZhang, JunJ. (2009). On recovery of sparse signals via ℓ 1 \ell_{1} minimization. IEEE Trans. Inform. Theory 55 3388–3397
2009
Earlier work this paper cites.
Candès, Emmanuel J.E. J. andRecht, BenjaminB. (2009). Exact matrix completion via convex optimization. Found. Comput. Math. 9 717–772
2009
Earlier work this paper cites.
Koren, Y.Y., Bell, R.R. andVolinsky, C.C. (2009). Matrix factorization techniques for recommender systems. Computer 42 30–37
2009
Earlier work this paper cites.
Dvijotham, K.K. andFazel, M.M. (2010). A nullspace analysis of the nuclear norm heuristic for rank minimization. In 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP) 3586–3589
2010
Earlier work this paper cites.
Gross, D.D., Liu, Y. K.Y. K., Flammia, S. T.S. T., Becker, S.S. andEisert, J.J. (2010). Quantum state tomography via compressed sensing. Phys. Rev. Lett. 105 150401–150404
2010
Cited alongside, same era.
Nadler, BoazB. (2010). Nonparametric detection of signals by information theoretic criteria: Performance analysis and an improved estimator. IEEE Trans. Signal Process. 58 2746–2756
2010
Cited alongside, same era.
2010
Cited alongside, same era.
Recht, BenjaminB., Fazel, MaryamM. andParrilo, Pablo A.P. A. (2010). Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization. SIAM Rev. 52 471–501
2010
Cited alongside, same era.
Alquier, P.P., Butucea, C.C., Hebiri, M.M. andMeziani, K.K. (2013). Rank penalized estimation of a quantum system. Phys. Rev. A. 88 032133
2013
Closest in time.
Birnbaum, AharonA., Johnstone, Iain M.I. M., Nadler, BoazB. andPaul, DebashisD. (2013). Minimax bounds for sparse PCA with noisy high-dimensional data. Ann. Statist. 41 1055–1084
2013
Closest in time.
Cai, T. TonyT. T., Ma, ZongmingZ. andWu, YihongY. (2013). Sparse PCA: Optimal rates and adaptive estimation. Ann. Statist. 41 3074–3110
2013
Closest in time.
Cai, T. TonyT. T. andZhang, AnruA. (2013). Sharp RIP bound for sparse signal and low-rank matrix recovery. Appl. Comput. Harmon. Anal. 35 74–93
2013
Closest in time.
Cai, T. TonyT. T. andZhang, AnruA. (2013). Compressed sensing and affine rank minimization under restricted isometry. IEEE Trans. Signal Process. 61 3279–3290
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2011
Cited alongside, same era.
Candès, Emmanuel J.E. J. andPlan, YanivY. (2011). Tight oracle inequalities for low-rank matrix recovery from a minimal number of noisy random measurements. IEEE Trans. Inform. Theory 57 2342–2359
2011
Cited alongside, same era.
Koltchinskii, VladimirV., Lounici, KarimK. andTsybakov, Alexandre B.A. B. (2011). Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion. Ann. Statist. 39 2302–2329
2011
Cited alongside, same era.
Negahban, SahandS. andWainwright, Martin J.M. J. (2011). Estimation of (near) low-rank matrices with noise and high-dimensional scaling. Ann. Statist. 39 1069–1097
2011
Cited alongside, same era.
binproceedings Oymak, S.S., Mohan, K.K., Fazel, M.M. andHassibi, B.B. (2011). A simplified approach to recovery conditions for low-rank matrices. In Proc. Intl. Sympo. Information Theory (ISIT) 2318–2322. IEEE, Piscataway, NJ
2011
Cited alongside, same era.
Recht, BenjaminB. (2011). A simpler approach to matrix completion. J. Mach. Learn. Res. 12 3413–3430
2011
Cited alongside, same era.
Rohde, AngelikaA. andTsybakov, Alexandre B.A. B. (2011). Estimation of high-dimensional low-rank matrices. Ann. Statist. 39 887–930
2011
Cited alongside, same era.
Vershynin, RomanR. (2011). Spectral norm of products of random and deterministic matrices. Probab. Theory Related Fields 150 471–509
2011
Cited alongside, same era.
2013
Closest in time.
Candès, Emmanuel J.E. J., Strohmer, ThomasT. andVoroninski, VladislavV. (2013). PhaseLift: Exact and stable signal recovery from magnitude measurements via convex programming. Comm. Pure Appl. Math. 66 1241–1274
2013
Closest in time.
2013
Closest in time.
2013
Closest in time.
Wang, H.H. andLi, S.S. (2013). The bounds of restricted isometry constants for low rank matrices recovery. Sci. China Ser. A 56 1117–1127
2013
Closest in time.
Wang, YazhenY. (2013). Asymptotic equivalence of quantum state tomography and noisy matrix completion. Ann. Statist. 41 2462–2504
2013
Closest in time.
Cai, T. TonyT. T., Ma, ZongmingZ. andWu, YihongY. (2014). Optimal estimation and rank detection for sparse spiked covariance matrices. Probab. Theory Related Fields. To appear
2014
Closest in time.
Cai, T. TonyT. T. andZhang, AnruA. (2014). Sparse representation of a polytope and recovery in sparse signals and low-rank matrices. IEEE Trans. Inform. Theory 60 122–132
2014
Closest in time.
Cai, T. andZhang, A. (2014). Supplement to “ROP: Matrix recovery via rank-one projections.” DOI: \doiurl
2014
Closest in time.
Candès, Emmanuel J.E. J. andTao, TerenceT. (2010). The power of convex relaxation: Near-optimal matrix completion. IEEE Trans. Inform. Theory 56 2053–2080
2080
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