-
1
-
-
46249124832
-
Consistency of trace norm minimization
-
Bach, F. (2008). Consistency of trace norm minimization. Journal of Machine Learning Research, 9, 1019-1048.
-
(2008)
Journal of Machine Learning Research
, vol.9
, pp. 1019-1048
-
-
Bach, F.1
-
2
-
-
21644465788
-
Local minima and convergence in low-rank semidefinite programming
-
Burer, S.,& Monteiro, R. (2005). Local minima and convergence in low-rank semidefinite programming. Mathematical Programming, 103, 427-444.
-
(2005)
Mathematical Programming
, vol.103
, pp. 427-444
-
-
Burer, S.1
Monteiro, R.2
-
3
-
-
77951291046
-
A singular value thresholding algorithm for matrix completion
-
Cai, J., Candés, E., & Shen, Z. (2010). A singular value thresholding algorithm for matrix completion. SIAM Journal on Optimization, 20(4), 1956-1982.
-
(2010)
SIAM Journal on Optimization
, vol.20
, Issue.4
, pp. 1956-1982
-
-
Cai, J.1
Candés, E.2
Shen, Z.3
-
5
-
-
79960675858
-
Robust principal component analysis?
-
Candès, E., Li, X., Ma, Y., & Wright, J. (2009). Robust principal component analysis? Journal of the ACM, 58(3), 1-37.
-
(2009)
Journal of the ACM
, vol.58
, Issue.3
, pp. 1-37
-
-
Candès, E.1
Li, X.2
Ma, Y.3
Wright, J.4
-
6
-
-
77952741387
-
Matrix completion with noise
-
Cand̀es, E., & Plan, Y. (2010). Matrix completion with noise. IEEE Proceedings, 98, 925-936.
-
(2010)
IEEE Proceedings
, vol.98
, pp. 925-936
-
-
Cand̀es, E.1
Plan, Y.2
-
7
-
-
71049116435
-
Exact matrix completion via convex optimization
-
Candès, E., & Recht, B. (2009). Exact matrix completion via convex optimization. Foundations of Computational Mathematics, 9(6), 717-772.
-
(2009)
Foundations of Computational Mathematics
, vol.9
, Issue.6
, pp. 717-772
-
-
Candès, E.1
Recht, B.2
-
8
-
-
79960591511
-
Rank-sparsity incoherence for matrix decomposition
-
Chandrasekaran, V., Sanghavi, S., Parrilo, P., & Willsky, A. (2009). Rank-sparsity incoherence for matrix decomposition. SIAM Journal on Optimization, 21(2), 572-596.
-
(2009)
SIAM Journal on Optimization
, vol.21
, Issue.2
, pp. 572-596
-
-
Chandrasekaran, V.1
Sanghavi, S.2
Parrilo, P.3
Willsky, A.4
-
9
-
-
0032216898
-
The geometry of algorithms with orthogonality constraints
-
Edelman, A., Arias, T., & Smith, S. (1999). The geometry of algorithms with orthogonality constraints. SIAM Journal onMatrix Analysis and Applications, 20, 303-353.
-
(1999)
SIAM Journal onMatrix Analysis and Applications
, vol.20
, pp. 303-353
-
-
Edelman, A.1
Arias, T.2
Smith, S.3
-
11
-
-
79960425522
-
Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
-
Halko, N., Martinsson, P., & Tropp, J. (2011). Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions. SIAM Review, 53(2), 217-288.
-
(2011)
SIAM Review
, vol.53
, Issue.2
, pp. 217-288
-
-
Halko, N.1
Martinsson, P.2
Tropp, J.3
-
12
-
-
84874198046
-
-
Manchester: Department of Mathematics, Manchester University
-
Higham, N. (1995). Matrix procrustes problems (Tech. Rep.). Manchester: Department of Mathematics, Manchester University.
-
(1995)
Matrix procrustes problems (Tech. Rep.)
-
-
Higham, N.1
-
14
-
-
18144420071
-
Acquiring linear subspaces for face recognition under variable lighting
-
Lee, K. C., Ho, J., & Kriegman, D. (2005). Acquiring linear subspaces for face recognition under variable lighting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(5), 684-698.
-
(2005)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.27
, Issue.5
, pp. 684-698
-
-
Lee, K.C.1
Ho, J.2
Kriegman, D.3
-
15
-
-
84965096924
-
-
Champaign: Department of Electrical and Computer Engineering, University of Illinois
-
Lin, Z., Chen, M., Wu, L., & Ma, Y. (2009). The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices (Tech. Rep., UILU-ENG-09-2215). Champaign: Department of Electrical and Computer Engineering, University of Illinois.
-
(2009)
The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices (Tech. Rep., UILU-ENG-09-2215)
-
-
Lin, Z.1
Chen, M.2
Wu, L.3
Ma, Y.4
-
16
-
-
85162350693
-
Linearized alternating direction method with adaptive penalty for low-rank representation
-
J. Shawe-Taylor, R. S. Zemel, P. Bartlett, F.C.N. Pereira,& K.Q.Weinberger (Eds.), Red Hook, NY: Curran.
-
Lin, Z., Liu,R.,& Su, Z. (2011). Linearized alternating direction method with adaptive penalty for low-rank representation. In J. Shawe-Taylor, R. S. Zemel, P. Bartlett, F.C.N. Pereira,& K.Q.Weinberger (Eds.), Advances in neural information processing systems, 24 (pp. 612-620). Red Hook, NY: Curran.
-
(2011)
Advances in neural information processing systems
, vol.24
, pp. 612-620
-
-
Lin, Z.1
Liu, R.2
Su, Z.3
-
17
-
-
84865420055
-
Robust recovery of subspace structures by low-rank representation
-
Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., & Ma, Y. (2012). Robust recovery of subspace structures by low-rank representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 99, 28-42.
-
(2012)
IEEE Transactions on Pattern Analysis and Machine Intelligence
, vol.99
, pp. 28-42
-
-
Liu, G.1
Lin, Z.2
Yan, S.3
Sun, J.4
Yu, Y.5
Ma, Y.6
-
18
-
-
77956529193
-
Robust subspace segmentation by low-rank representation
-
Madison,WI: Omnipress.
-
Liu, G., Lin, Z., & Yu, Y. (2010). Robust subspace segmentation by low-rank representation. In Proceedings of the 27th International Conference on Machine Learning (pp. 663-670). Madison,WI: Omnipress.
-
(2010)
Proceedings of the 27th International Conference on Machine Learning
, pp. 663-670
-
-
Liu, G.1
Lin, Z.2
Yu, Y.3
-
19
-
-
78651312555
-
Decomposing background topics from keywords by principal component pursuit
-
New York: ACM.
-
Min, K., Zhang, Z.,Wright, J., & Ma, Y. (2010). Decomposing background topics from keywords by principal component pursuit. In Proceedings of the 28th Conference on Information and Knowledge Management (pp. 269-278). New York: ACM.
-
(2010)
Proceedings of the 28th Conference on Information and Knowledge Management
, pp. 269-278
-
-
Min, K.1
Zhang, Z.2
Wright, J.3
Ma, Y.4
-
21
-
-
80053458764
-
Large-scale convex minimization with a low-rank constraint
-
Madison,WI: Omnipress.
-
Shalev-Shwartz, S., Gonen, A.,& Shamir,O. (2011). Large-scale convex minimization with a low-rank constraint. In Proceedings of the 28th International Conference on Machine Learning (pp. 329-336). Madison, WI: Omnipress.
-
(2011)
Proceedings of the 28th International Conference on Machine Learning
, pp. 329-336
-
-
Shalev-Shwartz, S.1
Gonen, A.2
Shamir, O.3
-
22
-
-
84866035233
-
-
Houston, TX: Department of Computational and Applied Mathematics, Rice University.
-
Shen, Y., Wen, Z., & Zhang, Y. (2011). Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization (Tech. Rep.). Houston, TX: Department of Computational and Applied Mathematics, Rice University.
-
(2011)
Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization (Tech. Rep.)
-
-
Shen, Y.1
Wen, Z.2
Zhang, Y.3
-
23
-
-
26944475424
-
Generalization error bounds for collaborative prediction with low-rank matrices
-
L. K. Saul, Y.Weiss, & L. Bottou (Eds.), Cambridge, MA: MIT Press.
-
Srebro,N., Alon,N.,& Jaakkola, T. (2005). Generalization error bounds for collaborative prediction with low-rank matrices. In L. K. Saul, Y.Weiss, & L. Bottou (Eds.), Advances in Neural Information Processing Systems, 17 (pp. 5-27). Cambridge, MA: MIT Press.
-
(2005)
Advances in Neural Information Processing Systems
, vol.17
, pp. 5-27
-
-
Srebro, N.1
Alon, N.2
Jaakkola, T.3
-
24
-
-
77956529188
-
A fast augmented Lagrangian algorithm for learning low-rank matrices
-
Madison, WI: Omnipress.
-
Tomioka, R., Suzuki, T., Sugiyama, M., & Kashima, H. (2010). A fast augmented Lagrangian algorithm for learning low-rank matrices. In Proceedings of the 27th International Conference on Machine Learning (pp. 1087-1094). Madison, WI: Omnipress.
-
(2010)
Proceedings of the 27th International Conference on Machine Learning
, pp. 1087-1094
-
-
Tomioka, R.1
Suzuki, T.2
Sugiyama, M.3
Kashima, H.4
-
26
-
-
48349104603
-
Cofi rank: Maximum margin matrix factorization for collaborative ranking
-
J. C. Platt, D. Köller, Y. Singer, & S. T. Roweis (Eds.), Cambridge, MA: MIT Press.
-
Weimer, M., Karatzoglou, A., Le, Q., & Smola, A. (2007). Cofi rank: Maximum margin matrix factorization for collaborative ranking. In J. C. Platt, D. Köller, Y. Singer, & S. T. Roweis (Eds.), Advances in Neural Information Processing Systems, 20. Cambridge, MA: MIT Press.
-
(2007)
Advances in Neural Information Processing Systems
, vol.20
-
-
Weimer, M.1
Karatzoglou, A.2
Le, Q.3
Smola, A.4
-
27
-
-
0039722607
-
The effect of the input density distribution on kernel-based classifiers
-
San Francisco: Morgan Kaufmann.
-
Williams, C., & Seeger, M. (2000). The effect of the input density distribution on kernel-based classifiers. In Proceedings of the 17th International Conference on Machine Learning (pp. 1159-1166). San Francisco: Morgan Kaufmann.
-
(2000)
Proceedings of the 17th International Conference on Machine Learning
, pp. 1159-1166
-
-
Williams, C.1
Seeger, M.2
-
28
-
-
84863367863
-
Robust principal component analysis: Exact recovery of corrupted low-rank matrices via convex optimization
-
Y. Bengio, D. Schuurmans, J. D. Lafferty, C.K.I. Williams, & A. Culotta (Eds.), Red Hook, NY: Curran.
-
Wright, J., Ganesh, A., Rao, S., Peng, Y., & Ma, Y. (2009). Robust principal component analysis: Exact recovery of corrupted low-rank matrices via convex optimization. In Y. Bengio, D. Schuurmans, J. D. Lafferty, C.K.I. Williams, & A. Culotta (Eds.), Advances in neural information processing systems, 22 (pp. 2080-2088). Red Hook, NY: Curran.
-
(2009)
Advances in neural information processing systems
, vol.22
, pp. 2080-2088
-
-
Wright, J.1
Ganesh, A.2
Rao, S.3
Peng, Y.4
Ma, Y.5
-
29
-
-
78149332597
-
An inexact alternating direction method for trace norm regularized least squares problem
-
(forthcoming)
-
Yang, J., & Yuan, X. (forthcoming). An inexact alternating direction method for trace norm regularized least squares problem. Mathematics of Computation.
-
Mathematics of Computation
-
-
Yang, J.1
Yuan, X.2
-
31
-
-
84862826891
-
TILT: Transform invariant low-rank textures
-
Zhang, Z., Liang, X., Ganesh, A.,& Ma, Y. (2012). TILT: Transform invariant low-rank textures. International Journal of Computer Vision, 99(1), 314-328.
-
(2012)
International Journal of Computer Vision
, vol.99
, Issue.1
, pp. 314-328
-
-
Zhang, Z.1
Liang, X.2
Ganesh, A.3
Ma, Y.4
-
32
-
-
78650977486
-
Image tag refinement towards low-rank, content-tag prior and error sparsity
-
New York: ACM.
-
Zhu, G., Yan, S.,& Ma, Y. (2010). Image tag refinement towards low-rank, content-tag prior and error sparsity. In Proceedings of the 18th ACM Conference on Multimedia. New York: ACM.
-
(2010)
Proceedings of the 18th ACM Conference on Multimedia
-
-
Zhu, G.1
Yan, S.2
Ma, Y.3
|