-
2
-
-
84862609231
-
Computing a nonnegative matrix factorization -Provably
-
New York, NY, USA. ACM
-
S. Arora, R. Ge, R. Kannan, and A. Moitra. Computing a nonnegative matrix factorization -provably. In Proceedings of the 44th Symposium on Theory of Computing, STOC '12, pages 145-162, New York, NY, USA, 2012. ACM.
-
(2012)
Proceedings of the 44th Symposium on Theory of Computing, STOC '12
, pp. 145-162
-
-
Arora, S.1
Ge, R.2
Kannan, R.3
Moitra, A.4
-
4
-
-
84856262691
-
Perturbation of matrices and non-negative rank with a view toward statistical models
-
C. Bocci, E. Carlini, and F. Rapallo. Perturbation of matrices and non-negative rank with a view toward statistical models. SIAM. J. Matrix Anal. & Appl., 32(4):1500-1512, 2011.
-
(2011)
SIAM. J. Matrix Anal. & Appl
, vol.324
, pp. 1500-1512
-
-
Bocci, C.1
Carlini, E.2
Rapallo, F.3
-
5
-
-
70349152160
-
An improved approximation algorithm for the column subset selection problem
-
Philadelphia, PA, USA,. Society for Industrial and Applied Mathematics
-
C. Boutsidis, M.W. Mahoney, and P. Drineas. An improved approximation algorithm for the column subset selection problem. In Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA '09, pages 968-977, Philadelphia, PA, USA, 2009. Society for Industrial and Applied Mathematics.
-
(2009)
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA '09
, pp. 968-977
-
-
Boutsidis, C.1
Mahoney, M.W.2
Drineas, P.3
-
6
-
-
55549091744
-
Low-dimensional polytope approximation and its applications to nonnegative matrix factorization
-
M.T. Chu and M.M. Lin. Low-dimensional polytope approximation and its applications to nonnegative matrix factorization. SIAM J. Sci. Comput., 30(3):1131-1155, 2008.
-
(2008)
SIAM J. Sci. Comput
, vol.30
, Issue.3
, pp. 1131-1155
-
-
Chu, M.T.1
Lin, M.M.2
-
8
-
-
0028427066
-
Minimum-volume tranforms for remotely sensed data
-
M.D. Craig. Minimum-volume tranforms for remotely sensed data. IEEE Trans. On Geoscience and Remote Sensing, 32(3):542-552, 1994.
-
(1994)
IEEE Trans. On Geoscience and Remote Sensing
, vol.32
, Issue.3
, pp. 542-552
-
-
Craig, M.D.1
-
9
-
-
33749255098
-
On the equivalence of nonnegative matrix factorization and spectral clustering. In
-
C. Ding, X. He, and H.D. Simon. On the equivalence of nonnegative matrix factorization and spectral clustering. In SIAM Int. Conf. Data Mining (SDM'05), pages 606-610, 2005.
-
(2005)
SIAM Int. Conf. Data Mining (SDM'05)
, pp. 606-610
-
-
Ding, C.1
He, X.2
Simon, H.D.3
-
10
-
-
33749575326
-
Orthogonal nonnegative matrix tri-factorizations for clustering
-
KDD 2006: Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
-
C. Ding, T. Li, W. Peng, and H. Park. Orthogonal nonnegative matrix tri-factorizations for clustering. In In Proc. Of the 12th ACM SIGKDD Int. Conf. On Knowledge Discovery and Data Mining, pages 126-135, 2006. (Pubitemid 44535510)
-
(2006)
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, vol.2006
, pp. 126-135
-
-
Ding, C.1
Li, T.2
Peng, W.3
Park, H.4
-
11
-
-
23744456750
-
When does non-negative matrix factorization give a correct decomposition into parts?
-
D. Donoho and V. Stodden. When does non-negative matrix factorization give a correct decomposition into parts? In Advances in Neural Information Processing Systems 16, 2003.
-
(2003)
Advances in Neural Information Processing Systems
, vol.16
-
-
Donoho, D.1
Stodden, V.2
-
12
-
-
63249085556
-
Nonnegative matrix factorization with the itakura-saito divergence: With application to music analysis
-
C. F́evotte, N. Bertin, and J.L. Durrieu. Nonnegative matrix factorization with the itakura-saito divergence: With application to music analysis. Neural Computation, 21(3):793-830, 2009.
-
(2009)
Neural Computation
, vol.21
, Issue.3
, pp. 793-830
-
-
F́evotte, C.1
Bertin, N.2
Durrieu, J.L.3
-
15
-
-
74449083451
-
Using underapproximations for sparse nonnegative matrix factorization
-
N. Gillis and F. Glineur. Using underapproximations for sparse nonnegative matrix factorization. Pattern Recognition, 43(4):1676-1687, 2010.
-
(2010)
Pattern Recognition
, vol.43
, Issue.4
, pp. 1676-1687
-
-
Gillis, N.1
Glineur, F.2
-
16
-
-
84865687533
-
On the geometric interpretation of the nonnegative rank
-
N. Gillis and F. Glineur. On the geometric interpretation of the nonnegative rank. Linear Algebra and its Applications, 437(11):2685-2712, 2012a.
-
(2012)
Linear Algebra and its Applications
, vol.437
, Issue.11
, pp. 2685-2712
-
-
Gillis, N.1
Glineur, F.2
-
17
-
-
84861111031
-
Accelerated multiplicative updates and hierarchical als algorithms for nonnegative matrix factorization
-
N. Gillis and F. Glineur. Accelerated multiplicative updates and hierarchical ALS algorithms for nonnegative matrix factorization. Neural Computation, 24(4):1085-1105, 2012b.
-
(2012)
Neural Computation
, vol.24
, Issue.4
, pp. 1085-1105
-
-
Gillis, N.1
Glineur, F.2
-
20
-
-
84900510076
-
Nonnegative matrix factorization with sparseness constraints
-
P.O. Hoyer. Nonnegative matrix factorization with sparseness constraints. J. Machine Learning Research, 5:1457-1469, 2004.
-
(2004)
J. Machine Learning Research
, vol.5
, pp. 1457-1469
-
-
Hoyer, P.O.1
-
21
-
-
77952582975
-
Minimum dispersion constrained nonnegative matrix factorization to unmix hyperspectral data
-
A. Huck, M. Guillaume, and J. Blanc-Talon. Minimum dispersion constrained nonnegative matrix factorization to unmix hyperspectral data. IEEE Trans. On Geoscience and Remote Sensing, 48 (6):2590-2602, 2010.
-
(2010)
IEEE Trans. On Geoscience and Remote Sensing
, vol.48
, Issue.6
, pp. 2590-2602
-
-
Huck, A.1
Guillaume, M.2
Blanc-Talon, J.3
-
23
-
-
34547844077
-
Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis
-
DOI 10.1093/bioinformatics/btm134
-
H. Kim and H. Park. Sparse non-negative matrix factorizations via alternating non-negativityconstrained least squares for microarray data analysis. Bioinformatics, 23(12):1495-1502, 2007. (Pubitemid 47244474)
-
(2007)
Bioinformatics
, vol.23
, Issue.12
, pp. 1495-1502
-
-
Kim, H.1
Park, H.2
-
24
-
-
58249092020
-
Non-negative matrix factorization: Ill-posedness and a geometric algorithm
-
B. Klingenberg, J. Curry, and A. Dougherty. Non-negative matrix factorization: Ill-posedness and a geometric algorithm. Pattern Recognition, 42(5):918-928, 2009.
-
(2009)
Pattern Recognition
, vol.42
, Issue.5
, pp. 918-928
-
-
Klingenberg, B.1
Curry, J.2
Dougherty, A.3
-
25
-
-
47649123078
-
Theorems on positive data: On the uniqueness of nmf
-
Article ID 764206
-
H. Laurberg, M.G. Christensen, M.D. Plumbley, L.K. Hansen, and S.H. Jensen. Theorems on positive data: On the uniqueness of NMF. Computational Intelligence and Neuroscience, 2008. Article ID 764206.
-
(2008)
Computational Intelligence and Neuroscience
-
-
Laurberg, H.1
Christensen, M.G.2
Plumbley, M.D.3
Hansen, L.K.4
Jensen, S.H.5
-
26
-
-
0033592606
-
Learning the parts of objects by nonnegative matrix factorization
-
D.D. Lee and H.S. Seung. Learning the parts of objects by nonnegative matrix factorization. Nature, 401:788-791, 1999.
-
(1999)
Nature
, vol.401
, pp. 788-791
-
-
Lee, D.D.1
Seung, H.S.2
-
27
-
-
33847733865
-
Endmember extraction from highly mixed data using minimum volume constrained nonnegative matrix factorization
-
DOI 10.1109/TGRS.2006.888466
-
L. Miao and H. Qi. Endmember extraction from highly mixed data using minimum volume constrained nonnegative matrix factorization. IEEE Trans. On Geoscience and Remote Sensing, 45 (3):765-777, 2007. (Pubitemid 46375748)
-
(2007)
IEEE Transactions on Geoscience and Remote Sensing
, vol.45
, Issue.3
, pp. 765-777
-
-
Miao, L.1
Qi, H.2
-
28
-
-
0028561099
-
Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values
-
P. Paatero and U. Tapper. Positive matrix factorization: a non-negative factor model with optimal utilization of error estimates of data values. Environmetrics, 5:111-126, 1994.
-
(1994)
Environmetrics
, vol.5
, pp. 111-126
-
-
Paatero, P.1
Tapper, U.2
-
29
-
-
33646682646
-
Nonnegative matrix factorization for spectral data analysis
-
DOI 10.1016/j.laa.2005.06.025, PII S002437950500340X
-
V.P. Pauca, J. Piper, and R.J. Plemmons. Nonnegative matrix factorization for spectral data analysis. Linear Algebra and its Applications, 406(1):29-47, 2006. (Pubitemid 43737212)
-
(2006)
Linear Algebra and Its Applications
, vol.416
, Issue.1
, pp. 29-47
-
-
Pauca, V.P.1
Piper, J.2
Plemmons, R.J.3
-
30
-
-
18844398597
-
Hard problems in linear control theory: Possible approaches to solution
-
DOI 10.1007/s10513-005-0115-0
-
B.T. Polyak and P.S. Shcherbakov. Hard problems in linear control theory: Possible approaches to solution. Automation and Remote Control, 66:681-718, 2005. (Pubitemid 40683646)
-
(2005)
Automation and Remote Control
, vol.66
, Issue.5
, pp. 681-718
-
-
Polyak, B.T.1
Shcherbakov, P.S.2
-
32
-
-
78549288866
-
Guaranteed minimum rank solutions to linear matrix equations via nuclear norm minimization
-
G.B. Recht, M. Fazel, and P.A. Parrilo. Guaranteed minimum rank solutions to linear matrix equations via nuclear norm minimization. SIAM Review, 52(3):471-501, 2010.
-
(2010)
SIAM Review
, vol.523
, pp. 471-501
-
-
Recht, G.B.1
Fazel, M.2
Parrilo, P.A.3
-
33
-
-
80052705373
-
Underdetermined sparse blind source separation of nonnegative and partially overlapped data
-
Y. Sun and J. Xin. Underdetermined sparse blind source separation of nonnegative and partially overlapped data. SIAM Journal on Scientific Computing, 33(4):2063-2094, 2011.
-
(2011)
SIAM Journal on Scientific Computing
, vol.334
, pp. 2063-2094
-
-
Sun, Y.1
Xin, J.2
-
34
-
-
0000004244
-
A recurring theorem on determinants
-
O. Taussky. A recurring theorem on determinants. The American Mathematical Monthly, 56(10): 672-676, 1949.
-
(1949)
The American Mathematical Monthly
, vol.56
, Issue.10
, pp. 672-676
-
-
Taussky, O.1
-
35
-
-
84863658880
-
First results on uniqueness of sparse non-negative matrix factorization
-
EUSIPCO, Antalya, Turkey
-
F.J. Theis, K. Stadlthanner, and T. Tanaka. First results on uniqueness of sparse non-negative matrix factorization. In 13th European Signal Processing Conference, EUSIPCO, Antalya, Turkey, 2005.
-
(2005)
13th European Signal Processing Conference
-
-
Theis, F.J.1
Stadlthanner, K.2
Tanaka, T.3
-
36
-
-
0039889366
-
Rank factorization of nonnegative matrices
-
L.B. Thomas. Rank factorization of nonnegative matrices. SIAM Review, 16(3):393-394, 1974.
-
(1974)
SIAM Review
, vol.16
, Issue.3
, pp. 393-394
-
-
Thomas, L.B.1
-
37
-
-
73249153369
-
On the complexity of nonnegative matrix factorization
-
S.A. Vavasis. On the complexity of nonnegative matrix factorization. SIAM J. On Optimization, 20 (3):1364-1377, 2009.
-
(2009)
SIAM J. On Optimization
, vol.20
, Issue.3
, pp. 1364-1377
-
-
Vavasis, S.A.1
-
38
-
-
77949836282
-
Nonnegative least-correlated component analysis for separation of dependent sources by volume maximization
-
F.-Y. Wang, C.-Y. Chi, T.-H. Chan, and Y. Wang. Nonnegative least-correlated component analysis for separation of dependent sources by volume maximization. IEEE Trans. On Pattern Analysis and Machine Intelligence, 32(5):875-888, 2010.
-
(2010)
IEEE Trans. On Pattern Analysis and Machine Intelligence
, vol.325
, pp. 875-888
-
-
Wang, F.-Y.1
Chi, C.-Y.2
Chan, T.-H.3
Wang, Y.4
-
39
-
-
1542347778
-
Document clustering based on non-negative matrix factorization
-
New York, NY, USA. ACM
-
W. Xu, X. Liu, and Y. Gong. Document clustering based on non-negative matrix factorization. In Proc. Of the 26th Annual Int. ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '03, pages 267-273, New York, NY, USA, 2003. ACM.
-
(2003)
Proc. Of the 26th Annual Int. ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR '03
, pp. 267-273
-
-
Xu, W.1
Liu, X.2
Gong, Y.3
-
40
-
-
80053637334
-
Minimum-volume-constrained nonnegative matrix factorization: Enhanced ability of learning parts
-
G. Zhou, S. Xie, Z. Yang, J.-M. Yang, and Z. He. Minimum-volume- constrained nonnegative matrix factorization: Enhanced ability of learning parts. IEEE Trans. On Neural Networks, 22(10):1626-1637, 2011.
-
(2011)
IEEE Trans. On Neural Networks
, vol.2210
, pp. 1626-1637
-
-
Zhou, G.1
Xie, S.2
Yang, Z.3
Yang, J.-M.4
He, Z.5
|