-
1
-
-
34547198396
-
Algorithms and applications for approximate nonnegative matrix factorization
-
DOI 10.1016/j.csda.2006.11.006, PII S0167947306004191
-
M. Berry, M. Browne, A. Langville, V. Pauca, and R. Plemmons, Algorithms and applications for approximate nonnegative matrix factorization, Comput. Statist. Data Anal., 52 (2007), pp. 155-173. (Pubitemid 47331703)
-
(2007)
Computational Statistics and Data Analysis
, vol.52
, Issue.1
, pp. 155-173
-
-
Berry, M.W.1
Browne, M.2
Langville, A.N.3
Pauca, V.P.4
Plemmons, R.J.5
-
2
-
-
0642334046
-
A fast non-negativity-constrained least squares algorithm
-
R. Bro and S. De Jong, A fast non-negativity-constrained least squares algorithm, J. Chemometrics, 11 (1997), pp. 393-401. (Pubitemid 127478570)
-
(1997)
Journal of Chemometrics
, vol.11
, Issue.5
, pp. 393-401
-
-
Bro, R.1
De Jong, S.2
-
3
-
-
1642529511
-
Metagenes and molecular pattern discovery using matrix factorization
-
DOI 10.1073/pnas.0308531101
-
J. Brunet, P. Tamayo, T. Golub, and J. Mesirov, Metagenes and molecular pattern discovery using matrix factorization, Proc. Natl. Acad. Sci., 101 (2004), pp. 4164-4169. (Pubitemid 38405900)
-
(2004)
Proceedings of the National Academy of Sciences of the United States of America
, vol.101
, Issue.12
, pp. 4164-4169
-
-
Brunet, J.-P.1
Tamayo, P.2
Golub, T.R.3
Mesirov, J.P.4
-
5
-
-
74449093261
-
Fast local algorithms for large scale nonnegative matrix and tensor factorizations
-
A. Cichocki and A.-H. Phan, Fast local algorithms for large scale nonnegative matrix and tensor factorizations, IEICE Trans. Fundamentals Electron. Commun. Comput. Sci., E92-A (2009), pp. 708-721.
-
(2009)
IEICE Trans. Fundamentals Electron. Commun. Comput. Sci.
, vol.E92-A
, pp. 708-721
-
-
Cichocki, A.1
Phan, A.-H.2
-
6
-
-
37749030729
-
Hierarchical ALS algorithms for nonnegative matrix and 3d tensor factorization
-
Springer, New York
-
A. Cichocki, R. Zdunek, and S.-I. Amari, Hierarchical ALS algorithms for nonnegative matrix and 3d tensor factorization, in Independent Component Analysis and Signal Separation, Lecture Notes in Comput. Sci. 4666, Springer, New York, 2007, pp. 169-176.
-
(2007)
Independent Component Analysis and Signal Separation, Lecture Notes in Comput. Sci.
, vol.4666
, pp. 169-176
-
-
Cichocki, A.1
Zdunek, R.2
Amari, S.-I.3
-
7
-
-
84891283756
-
-
Wiley, Hoboken, NJ
-
A. Cichocki, R. Zdunek, A. H. Phan, and S.-I. Amari, Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation, Wiley, Hoboken, NJ, 2009.
-
(2009)
Nonnegative Matrix Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation
-
-
Cichocki, A.1
Zdunek, R.2
Phan, A.H.3
Amari, S.-I.4
-
8
-
-
48249151183
-
Nonnegative matrix factorization: An analytical and interpretive tool in computational biology
-
K. Devarajan, Nonnegative matrix factorization: An analytical and interpretive tool in computational biology, PLoS Comput. Biol., 4 (2008), e1000029.
-
(2008)
PLoS Comput. Biol.
, vol.4
-
-
Devarajan, K.1
-
9
-
-
84864031935
-
Generalized nonnegative matrix approximations with Bregman divergences
-
Y. Weiss, B. Schölkopf, and J. Platt, eds., MIT Press, Cambridge, MA
-
I. Dhillon and S. Sra, Generalized nonnegative matrix approximations with Bregman divergences, in Advances in Neural Information Processing Systems 18, Y. Weiss, B. Schölkopf, and J. Platt, eds., MIT Press, Cambridge, MA, 2006, pp. 283-290.
-
(2006)
Advances in Neural Information Processing Systems
, vol.18
, pp. 283-290
-
-
Dhillon, I.1
Sra, S.2
-
12
-
-
0033904057
-
On the convergence of the block nonlinear Gauss-Seidel method under convex constraints
-
DOI 10.1016/S0167-6377(99)00074-7
-
L. Grippo and M. Sciandrone, On the convergence of the block nonlinear Gauss-Seidel method under convex constraints, Oper. Res. Lett., 26 (2000), pp. 127-136. (Pubitemid 30564332)
-
(2000)
Operations Research Letters
, vol.26
, Issue.3
, pp. 127-136
-
-
Grippo, L.1
Sciandrone, M.2
-
14
-
-
0028434099
-
A block principal pivoting algorithm for large-scale strictly monotone linear complementarity problems
-
J. J. Júdice and F. M. Pires, A block principal pivoting algorithm for large-scale strictly monotone linear complementarity problems, Comput. Oper. Res., 21 (1994), pp. 587-596.
-
(1994)
Comput. Oper. Res.
, vol.21
, pp. 587-596
-
-
Júdice, J.J.1
Pires, F.M.2
-
15
-
-
56449106635
-
Fast Newton-type methods for the least squares nonnegative matrix approximation problem
-
SIAM, Philadelphia
-
D. Kim, S. Sra, and I. S. Dhillon, Fast Newton-type methods for the least squares nonnegative matrix approximation problem, in Proceedings of the Seventh SIAM International Conference on Data Mining, SIAM, Philadelphia, 2007, pp. 343-354.
-
(2007)
Proceedings of the Seventh SIAM International Conference on Data Mining
, pp. 343-354
-
-
Kim, D.1
Sra, S.2
Dhillon, I.S.3
-
16
-
-
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, Bioinform., 23 (2007), pp. 1495-1502. (Pubitemid 47244474)
-
(2007)
Bioinformatics
, vol.23
, Issue.12
, pp. 1495-1502
-
-
Kim, H.1
Park, H.2
-
17
-
-
67349093319
-
Nonnegative matrix factorization based on alternating nonnegativity constrained least squares and active set method
-
H. Kim and H. Park, Nonnegative matrix factorization based on alternating nonnegativity constrained least squares and active set method, SIAM J. Matrix Anal. Appl., 30 (2008), pp. 713-730.
-
(2008)
SIAM J. Matrix Anal. Appl.
, vol.30
, pp. 713-730
-
-
Kim, H.1
Park, H.2
-
20
-
-
84862300386
-
Fast active-set-type algorithms for l1-regularized linear regression
-
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS)
-
J. Kim and H. Park, Fast active-set-type algorithms for l1-regularized linear regression, in Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS), J. Mach. Learning Res. W&CP, 9 (2010), pp. 397-404.
-
J. Mach. Learning Res. W&CP
, vol.9
, Issue.2010
, pp. 397-404
-
-
Kim, J.1
Park, H.2
-
22
-
-
0033592606
-
Learning the parts of objects by non-negative matrix factorization
-
D. D. Lee and H. S. Seung, Learning the parts of objects by non-negative matrix factorization, Nature, 401 (1999), pp. 788-791.
-
(1999)
Nature
, vol.401
, pp. 788-791
-
-
Lee, D.D.1
Seung, H.S.2
-
23
-
-
84898964201
-
Algorithms for non-negative matrix factorization
-
MIT Press, Cambridge, MA
-
D. D. Lee and H. S. Seung, Algorithms for non-negative matrix factorization, in Advances in Neural Information Processing Systems 13, MIT Press, Cambridge, MA, 2001, pp. 556-562.
-
(2001)
Advances in Neural Information Processing Systems
, vol.13
, pp. 556-562
-
-
Lee, D.D.1
Seung, H.S.2
-
24
-
-
35548969471
-
Projected gradient methods for nonnegative matrix factorization
-
C.-J. Lin, Projected gradient methods for nonnegative matrix factorization, Neural Comput., 19 (2007), pp. 2756-2779.
-
(2007)
Neural Comput.
, vol.19
, pp. 2756-2779
-
-
Lin, C.-J.1
-
26
-
-
0035683536
-
Learning spatially localized, parts-based representation
-
S. Z. Li, X. Hou, H. Zhang, and Q. Cheng, Learning spatially localized, parts-based representation, in Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 1, 2001, pp. 207-212.
-
(2001)
Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
, vol.1
, pp. 207-212
-
-
Li, S.Z.1
Hou, X.2
Zhang, H.3
Cheng, Q.4
-
27
-
-
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 (1994), pp. 111-126.
-
(1994)
Environmetrics
, vol.5
, pp. 111-126
-
-
Paatero, P.1
Tapper, U.2
-
28
-
-
0030954231
-
Least squares formulation of robust non-negative factor analysis
-
DOI 10.1016/S0169-7439(96)00044-5, PII S0169743996000445
-
P. Paatero, Least squares formulation of robust non-negative factor analysis, Chemometrics Intell. Lab. Syst., 37 (1997), pp. 23-35. (Pubitemid 27242783)
-
(1997)
Chemometrics and Intelligent Laboratory Systems
, vol.37
, Issue.1
, pp. 23-35
-
-
Paatero, P.1
-
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 Appl., 416 (2006), pp. 29-47. (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
-
-
2942588993
-
Text mining using nonnegative matrix factorizations
-
SIAM, Philadelphia
-
V. P. Pauca, F. Shahnaz, M. W. Berry, and R. J. Plemmons, Text mining using nonnegative matrix factorizations, in Proceedings of the Fourth SIAM International Conference on Data Mining, SIAM, Philadelphia, 2004, pp. 452-456.
-
(2004)
Proceedings of the Fourth SIAM International Conference on Data Mining
, pp. 452-456
-
-
Pauca, V.P.1
Shahnaz, F.2
Berry, M.W.3
Plemmons, R.J.4
-
31
-
-
84968502344
-
A comparison of block pivoting and interior-point algorithms for linear least squares problems with nonnegative variables
-
L. F. Portugal, J. J. Judice, and L. N. Vicente, A comparison of block pivoting and interior-point algorithms for linear least squares problems with nonnegative variables, Math. Comp., 63 (1994), pp. 625-643.
-
(1994)
Math. Comp.
, vol.63
, pp. 625-643
-
-
Portugal, L.F.1
Judice, J.J.2
Vicente, L.N.3
-
32
-
-
0001287271
-
Regression shrinkage and selection via the lasso
-
R. Tibshirani, Regression shrinkage and selection via the lasso, J. Roy. Statist. Soc. Ser. B, 58 (1996), pp. 267-288.
-
(1996)
J. Roy. Statist. Soc. Ser. B
, vol.58
, pp. 267-288
-
-
Tibshirani, R.1
-
33
-
-
24944500827
-
Fast algorithm for the solution of large-scale non-negativity-constrained least squares problems
-
DOI 10.1002/cem.889
-
M. H. Van Benthem and M. R. Keenan, Fast algorithm for the solution of large-scale nonnegativity-constrained least squares problems, J. Chemometrics, 18 (2004), pp. 441-450. (Pubitemid 41327531)
-
(2004)
Journal of Chemometrics
, vol.18
, Issue.10
, pp. 441-450
-
-
Van Benthem, M.H.1
Keenan, M.R.2
-
34
-
-
73249153369
-
On the complexity of nonnegative matrix factorization
-
S. A. Vavasis, On the complexity of nonnegative matrix factorization, SIAM J. Optim., 20 (2009), pp. 1364-1377.
-
(2009)
SIAM J. Optim.
, vol.20
, pp. 1364-1377
-
-
Vavasis, S.A.1
-
35
-
-
1542347778
-
Document clustering based on non-negative matrix factorization
-
ACM Press, New York
-
W. Xu, X. Liu, and Y. Gong, Document clustering based on non-negative matrix factorization, in SIGIR '03: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM Press, New York, 2003, pp. 267-273.
-
(2003)
SIGIR '03: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
, pp. 267-273
-
-
Xu, W.1
Liu, X.2
Gong, Y.3
|