-
1
-
-
1642529511
-
Metagenes and molecular pattern discovery using matrix factorization
-
Mar
-
J.P. Brunei, P. Tamayo, T. R. Golub, and© EURASIP, 2010.J. P. Mesirov. Metagenes and molecular pattern discovery using matrix factorization. Proceedings of the National Academy of Sciences (PNAS), 101(12):4164- 4169, Mar 2004.
-
(2004)
Proceedings of the National Academy of Sciences (PNAS)
, vol.101
, Issue.12
, pp. 4164-4169
-
-
Brunei, J.P.1
Tamayo, P.2
Golub, T.R.3
Mesirov, J.P.4
-
2
-
-
0041974049
-
Marginal likelihood from the Gibbs output
-
Dec
-
S. Chib. Marginal likelihood from the Gibbs output. Journal of the American Statistical Association, 90(432):1313 1321, Dec 1995.
-
(1995)
Journal of the American Statistical Association
, vol.90
, Issue.432
, pp. 1313-1321
-
-
Chib, S.1
-
4
-
-
42149143421
-
Marginal likelihood estimation via power posteriors
-
N. Friel and A. N. Pettitt. Marginal likelihood estimation via power posteriors.© EURASIP, 2010.Journal of the Royal Statistical Society, 70(3):589 607, 2008.
-
(2008)
Journal of the Royal Statistical Society
, vol.70
, Issue.3
, pp. 589-607
-
-
Friel, N.1
Pettitt, A.N.2
-
6
-
-
0000736067
-
Simulating normalizing constants: From importance sampling to bridge sampling to path sampling
-
A. Gelman and X.-L. Meng. Simulating normalizing constants: From importance sampling to bridge sampling to path sampling. Statistical Science, 13(5): 163 185, 1998.
-
(1998)
Statistical Science
, vol.13
, Issue.5
, pp. 163-185
-
-
Gelman, A.1
Meng, X.-L.2
-
8
-
-
77956889087
-
Reversible jump markov chain monte carlo computation and bayesian model determination
-
P. J. Green. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrica, 82(4):711 732, 1995.".
-
(1995)
Biometrica
, vol.82
, Issue.4
, pp. 711-732
-
-
Green, P.J.1
-
11
-
-
1842486852
-
A split-merge markov chain monte carlo procedure for the dirichlet process mixture model
-
S. Iain and R. M. Neal. A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model. Journal of Computational and Graphical Statistics, 13(1):158 182, 2004.
-
(2004)
Journal of Computational and Graphical Statistics
, vol.13
, Issue.1
, pp. 158-182
-
-
Iain, S.1
Neal, R.M.2
-
12
-
-
70350175761
-
Fast projection-based methods for the least squares nonnegative matrix approximation problem
-
D. Kim, S. Sra, and S. Dhillon. Fast projection-based methods for the least squares nonnegative matrix approximation problem. Statistical Analysis and Data Mining, 1:38 51, 2008.
-
(2008)
Statistical Analysis and Data Mining
, vol.1
, pp. 38-51
-
-
Kim, D.1
Sra, S.2
Dhillon, S.3
-
13
-
-
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. Matrix Analysis and Applications, S1AM Journal on, 30(2):713 730, 2008.
-
(2008)
Matrix Analysis and Applications, S1AM Journal on
, vol.30
, Issue.2
, pp. 713-730
-
-
Kim, H.1
Park, H.2
-
14
-
-
38149041041
-
Inlinite sparse factor analysis and inlinite independent components analysis
-
volume 4666 of Lecture Notes in Computer Science Series (LNCS), Springer
-
D. Knowles and Z. Ghahramani. Inlinite sparse factor analysis and inlinite independent components analysis. In Independent Component Analysis and Signal Separation, International Conference on (1CA), volume 4666 of Lecture Notes in Computer Science Series (LNCS), pages 381 388. Springer, 2007.
-
(2007)
Independent Component Analysis and Signal Separation, International Conference on (1CA)
, pp. 381-388
-
-
Knowles, D.1
Ghahramani, Z.2
-
16
-
-
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(6755):788 791, 1999.
-
(1999)
Nature
, vol.401
, Issue.6755
, pp. 788-791
-
-
Lee, D.D.1
Seung, H.S.2
-
18
-
-
35548969471
-
Projcctcd gradient methods for non-negative matrix factorization
-
C.-J. Lin. Projcctcd gradient methods for non-negative matrix factorization. Neural Computation, 19:2756 2779, 2007.
-
(2007)
Neural Computation
, vol.19
, pp. 2756-2779
-
-
Lin, C.-J.1
-
20
-
-
84864028297
-
Modeling dyadic data with binary latent factors
-
Meeds, Z. Ghahramani, R. M. Neal, and S. T. Roweis. Modeling dyadic data with binary latent factors. In Advances in Neural Information Processing Systems (NIPS), volume 19, pages 977 984, 2007.
-
(2007)
Advances in Neural Information Processing Systems (NIPS)
, vol.19
, pp. 977-984
-
-
Meeds1
Ghahramani, Z.2
Neal, R.M.3
Roweis, S.T.4
-
22
-
-
33947514540
-
ERPWAVE- LAB a toolbox for multi-channel analysis of time-frequency transformed event related potentials
-
M. Mprup, L. K. Hansen, and S. M. Arnfred. ERPWAVE- LAB a toolbox for multi-channel analysis of time-frequency transformed event related potentials.© EURASIP, 2010.Journal of Neuro- science Methods, 161: (361 368), 2007.
-
(2007)
Journal of Neuro- Science Methods
, vol.161
, Issue.361-368
-
-
Mprup, M.1
Hansen, L.K.2
Arnfred, S.M.3
-
23
-
-
33750402597
-
Separation of non-negative mixture of non- negative sources using a Bayesian approach and MCMC sampling
-
Nov
-
S. Moussaoui, D. Brie, A. Mohammad-Djafari, and G. Carteret. Separation of non-negative mixture of non- negative sources using a Bayesian approach and MCMC sampling. Signal Processing, IEEE'lYansactions on, 54(11):4133 4145, Nov 2006.
-
(2006)
Signal Processing, IEEE'LYansactions on
, vol.54
, Issue.11
, pp. 4133-4145
-
-
Moussaoui, S.1
Brie, D.2
Mohammad-Djafari, A.3
Carteret, G.4
-
24
-
-
0033093826
-
A new method for spectral decomposition using a bilinear Bayesian approach
-
M. F. Ochs, R. S. Stoyanova, F. Arias-Mendoza, and T. R. Brown. A new method for spectral decomposition using a bilinear Bayesian approach.© EURASIP, 2010.Journal of Magnetic Resonance, 137:161 176, 1999.
-
(1999)
Journal of Magnetic Resonance
, vol.137
, pp. 161-176
-
-
Ochs, M.F.1
Stoyanova, R.S.2
Arias-Mendoza, F.3
Brown, T.R.4
-
25
-
-
0028561099
-
Positive matrix factorization: A nonnegative factor model with optimal utilization of error- estimates of data values
-
Jun
-
P. Paatero and U. Tapper. Positive matrix factorization: A nonnegative factor model with optimal utilization of error- estimates of data values. Enuironmetries, 5(2):111-126,© EURASIP, 2010.Jun 1994.
-
(1994)
Enuironmetries
, vol.5
, Issue.2
, pp. 111-126
-
-
Paatero, P.1
Tapper, U.2
-
26
-
-
33646682646
-
Nonnegative matrix factorization for spectral data analysis
-
Jul
-
V. P. Pauca, J. Piper, and R. J. Plemmons. Nonnegative matrix factorization for spectral data analysis. Linear Algebra and its Applications, 416(1):29 47, Jul 2006.
-
(2006)
Linear Algebra and Its Applications
, vol.416
, Issue.1
, pp. 29-47
-
-
Pauca, V.P.1
Piper, J.2
Plemmons, R.J.3
-
27
-
-
10044269618
-
Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic reso-nance chemical shift imaging of the brain
-
Dec
-
P. Sajda, S. Du, T. R. Brown, R. Stoyanova, D. C. Shungu, X. Mao, and L. C. Parra. Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain. Medical Imaging, IEEE Transactions on, 23(12):1453 1465, Dec 2004.
-
(2004)
Medical Imaging, IEEE Transactions on
, vol.23
, Issue.12
, pp. 1453-1465
-
-
Sajda, P.1
Du, S.2
Brown, T.R.3
Stoyanova, R.4
Shungu, D.C.5
Mao, X.6
Parra, L.C.7
-
28
-
-
1242263422
-
Recovery of constituent spectra using non-negative matrix factorization
-
P. Sajda, S. Du, and L. Parra. Recovery of constituent spectra using non-negative matrix factorization. In Wavelets: Applications in Signal and Image Processing, Proceedings of SP1E, volume 5207, pages 321 331, 2003.
-
(2003)
Wavelets: Applications in Signal and Image Processing, Proceedings of SP1E
, vol.5207
, pp. 321-331
-
-
Sajda, P.1
Du, S.2
Parra, L.3
-
30
-
-
84858072149
-
Probabilistic non-negative tensor factorization using Markov chain Monte Carlo
-
M. N. Schmidt and S. Mohamed. Probabilistic non-negative tensor factorization using Markov chain Monte Carlo. European Signal Processing Conference (EUS1PCO), pages 1918 1922, 2009.
-
(2009)
European Signal Processing Conference (EUS1PCO)
, pp. 1918-1922
-
-
Schmidt, M.N.1
Mohamed, S.2
-
31
-
-
33745711487
-
Nonnegative matrix factor 2-d deconvolution for blind single channel source separation
-
volume 3889 of Lecture Notes in Computer Science (LNCS), Springer, Apr
-
M. N. Schmidt and M. Mprup. Nonnegative matrix factor 2-d deconvolution for blind single channel source separation. In Independent Component Analysis and Blind Signal Separation, International Conference on (1CA), volume 3889 of Lecture Notes in Computer Science (LNCS), pages 700 707. Springer, Apr 2006.
-
(2006)
Independent Component Analysis and Blind Signal Separation, International Conference on (1CA)
, pp. 700-707
-
-
Schmidt, M.N.1
Mprup, M.2
-
32
-
-
67149090611
-
Bayesian non- negative matrix factorization
-
volume 5441 of Lecture Notes in Computer Science (LNCS), Springer
-
M. N. Schmidt, O. Winther, and L. K. Hansen. Bayesian non- negative matrix factorization. In Independent Component Analysis and Signal Separation, International Conference on (1CA), volume 5441 of Lecture Notes in Computer Science (LNCS), pages 540 547. Springer, 2009.
-
(2009)
Independent Component Analysis and Signal Separation, International Conference on (1CA)
, pp. 540-547
-
-
Schmidt, M.N.1
Winther, O.2
Hansen, L.K.3
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