-
2
-
-
68749121819
-
Sparse probabilistic projections
-
D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, editors Cambridge, MA, MIT Press
-
C. Archambeau and F. Bach. Sparse probabilistic projections. In D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, editors, Advances in Neural Information Processing Systems 21, pages 73-80, Cambridge, MA, 2009. MIT Press.
-
(2009)
Advances in Neural Information Processing Systems
, vol.21
, pp. 73-80
-
-
Archambeau, C.1
Bach, F.2
-
6
-
-
34548527584
-
Dynamic matrix-variate graphical models
-
C.M. Carvalho and M. West. Dynamic matrix-variate graphical models. Bayesian Analysis, 2: 69-98, 2007.
-
(2007)
Bayesian Analysis
, vol.2
, pp. 69-98
-
-
Carvalho, C.M.1
West, M.2
-
7
-
-
62549125109
-
High-dimensional sparse factor modelling: Applications in gene expression genomics
-
C.M. Carvalho, J.E. Lucas, Q. Wang, J.T. Chang, J.R. Nevins, and M. West. High-dimensional sparse factor modelling: Applications in gene expression genomics. Journal of the American Statistical Association, 103:1438-1456, 2008.
-
(2008)
Journal of the American Statistical Association
, vol.103
, pp. 1438-1456
-
-
Carvalho, C.M.1
Lucas, J.E.2
Wang, Q.3
Chang, J.T.4
Nevins, J.R.5
West, M.6
-
8
-
-
63649150787
-
Decomposing cellular signaling pathways into functional units: A genomic strategy
-
J. Chang, C.M. Carvalho, S. Mori, A. Bild, Q. Wang, M. West, and J.R. Nevins. Decomposing cellular signaling pathways into functional units: A genomic strategy. Molecular Cell, 34:104-114, 2009.
-
(2009)
Molecular Cell
, vol.34
, pp. 104-114
-
-
Chang, J.1
Carvalho, C.M.2
Mori, S.3
Bild, A.4
Wang, Q.5
West, M.6
Nevins, J.R.7
-
9
-
-
33750583269
-
Genomic prediction of loco-regional recurrence following mastectomy in breast cancer
-
S.H. Cheng, M. West C.F. Horng, E. Huang, J. Pittman, H. Dressman M.H. Tsou, C.M. Chen, S.Y. Tsail, J.J. Jian, J.R. Nevins M.C Liu, and A.T. Huang. Genomic prediction of loco-regional recurrence following mastectomy in breast cancer. Journal of Clinical Oncology, 24:4594-4602, 2006.
-
(2006)
Journal of Clinical Oncology
, vol.24
, pp. 4594-4602
-
-
Cheng, S.H.1
West, M.2
Horng, C.F.3
Huang, E.4
Pittman, J.5
Dressman, H.6
Tsou, M.H.7
Chen, C.M.8
Tsail, S.Y.9
Jian, J.J.10
Nevins, J.R.11
Liu, M.C.12
Huang, A.T.13
-
10
-
-
34548514458
-
A direct formulation for sparse PCA using semidefinite programming
-
A. d'Aspremont, L. El Ghaoui, M.I. Jordan, and G.R.G. Lanckriet. A direct formulation for sparse PCA using semidefinite programming. SIAM Review, 49(3):434-448, 2007.
-
(2007)
SIAM Review
, vol.49
, Issue.3
, pp. 434-448
-
-
D'Aspremont, A.1
El Ghaoui, L.2
Jordan, M.I.3
Lanckriet, G.R.G.4
-
11
-
-
15944399178
-
Sparse graphical models for exploring gene expression data
-
A. Dobra, B. Jones, C Hans, J.R. Nevins, and M. West. Sparse graphical models for exploring gene expression data. Journal of Multivariate Analysis, 90:196-212, 2004.
-
(2004)
Journal of Multivariate Analysis
, vol.90
, pp. 196-212
-
-
Dobra, A.1
Jones, B.2
Hans, C.3
Nevins, J.R.4
West, M.5
-
12
-
-
84864043341
-
Infinite latent feature models and the indian buffet process
-
Y. Weiss, B. Schölkopf, and J. Piatt, editors Cambridge, MA, MIT Press
-
T.L. Griffiths and Z Ghahramani. Infinite latent feature models and the indian buffet process. In Y. Weiss, B. Schölkopf, and J. Piatt, editors, Advances in Neural Information Processing Systems 18, pages 475-482, Cambridge, MA, 2006. MIT Press.
-
(2006)
Advances in Neural Information Processing Systems
, vol.18
, pp. 475-482
-
-
Griffiths, T.L.1
Ghahramani, Z.2
-
13
-
-
84862296954
-
Sparse probabilistic principal component analysis
-
Y. Guan and J Dy. Sparse probabilistic principal component analysis. Proceedings of AISTATS 2009,5:185-192, 2009.
-
(2009)
Proceedings of AISTATS 2009
, vol.5
, pp. 185192
-
-
Guan, Y.1
Dy, J.2
-
14
-
-
0003684449
-
-
Newv York: Springer
-
T. Hastie, R. Tibshirani, and J. Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Newv York: Springer, 2001.
-
(2001)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.3
-
15
-
-
41349101972
-
Statistical inference of transcriptional module-based gene networks from time course gene expression profiles by using state space models
-
O. Hirose, R. Yoshida, S. Imoto, R. Yamaguchi, T. Higuchi, D. S. Charnock-Jones, C Print, and S. Miyano. Statistical inference of transcriptional module-based gene networks from time course gene expression profiles by using state space models. Bioinformatics, 24(7):932-942, 2008.
-
(2008)
Bioinformatics
, vol.24
, Issue.7
, pp. 932-942
-
-
Hirose, O.1
Yoshida, R.2
Imoto, S.3
Yamaguchi, R.4
Higuchi, T.5
Charnock-Jones, D.S.6
Print, C.7
Miyano, S.8
-
16
-
-
0038244058
-
Gene expression predictors of breast cancer outcomes
-
E. Huang, S Chen, H. K. Dressman, J. Pittman, M. H. Tsou, C F Horng, A. Bild, E. S. Iversen, M. Liao, C M. Chen, M. West, J. R. Nevins, and A. T. Huang. Gene expression predictors of breast cancer outcomes. The Lancet, 361:1590-1596, 2003.
-
(2003)
The Lancet
, vol.361
, pp. 1590-1596
-
-
Huang, E.1
Chen, S.2
Dressman, H.K.3
Pittman, J.4
Tsou, M.H.5
Horng, C.F.6
Bild, A.7
Iversen, E.S.8
Liao, M.9
Chen, C.M.10
West, M.11
Nevins, J.R.12
Huang, A.T.13
-
17
-
-
0141941674
-
A modified principal component technique based on the lasso
-
I. T. Jolliffe, N. T. Trendafilov, and M. Uddin. A modified principal component technique based on the lasso. Journal of Computational and Graphical Statistics, 112(3):531-547, 2003.
-
(2003)
Journal of Computational and Graphical Statistics
, vol.112
, Issue.3
, pp. 531-547
-
-
Jolliffe, I.T.1
Trendafilov, N.T.2
Uddin, M.3
-
18
-
-
20144364427
-
Experiments in stochastic computation for high-dimensional graphical models
-
B. Jones, A. Dobra, C.M. Carvalho, C. Hans, C. Carter, and M. West. Experiments in stochastic computation for high-dimensional graphical models. Statistical Science, 20:388-400, 2005.
-
(2005)
Statistical Science
, vol.20
, pp. 388-400
-
-
Jones, B.1
Dobra, A.2
Carvalho, C.M.3
Hans, C.4
Carter, C.5
West, M.6
-
19
-
-
0004283231
-
-
M.I. Jordan, editor Cambridge MA: MIT Press
-
M.I. Jordan, editor. Learning in Graphical Models. Cambridge MA: MIT Press, 1999.
-
(1999)
Learning in Graphical Models
-
-
-
20
-
-
4043129651
-
Graphical models
-
M.I. Jordan. Graphical models. Statistical Science, 19:140-155, 2004.
-
(2004)
Statistical Science
, vol.19
, pp. 140-155
-
-
Jordan, M.I.1
-
21
-
-
1842830818
-
Evolutionary recombination hotspot around GSDML-GSDM locus is closely linked to the oncogenomic recombination hotspot around the PPP1R1B-ERBB2-GRB7 amplicon
-
M. Katoh and M. Katoh. Evolutionary recombination hotspot around GSDML-GSDM locus is closely linked to the oncogenomic recombination hotspot around the PPP1R1B-ERBB2-GRB7 amplicon. International Journal of Oncology, 24:757-763, 2004.
-
(2004)
International Journal of Oncology
, vol.24
, pp. 757-763
-
-
Katoh, M.1
Katoh, M.2
-
22
-
-
49549125943
-
Sparse statistical modelling in gene expression genomics
-
P. Müller, K.A. Do, and M. Vannucci, editors Cambridge University Press
-
J.E. Lucas, C.M. Carvalho, Q. Wang, A.H. Bild, J.R. Nevins, and M. West. Sparse statistical modelling in gene expression genomics. In P. Müller, K.A. Do, and M. Vannucci, editors, Bayesian Inference for Gene Expression and Proteomics, pages 155-176. Cambridge University Press, 2006.
-
(2006)
Bayesian Inference for Gene Expression and Proteomics
, pp. 155-176
-
-
Lucas, J.E.1
Carvalho, C.M.2
Wang, Q.3
Bild, A.H.4
Nevins, J.R.5
West, M.6
-
23
-
-
84887212455
-
Cross-study projections of genomic biomarkers: An evaluation in cancer genomics
-
J.E. Lucas, C.M. Carvalho, J-T.A. Chi, and M. West. Cross-study projections of genomic biomarkers: An evaluation in cancer genomics. PLoS ONE, 4(2):e4523, 2009.
-
(2009)
PLoS One
, vol.4
, Issue.2
-
-
Lucas, J.E.1
Carvalho, C.M.2
Chi, J.-T.A.3
West, M.4
-
24
-
-
0001441372
-
Probable networks and plausible predictions - A review of practical Bayesian methods for supervised neural networks
-
D.J.C Mackay. Probable networks and plausible predictions - a review of practical Bayesian methods for supervised neural networks. Network: Computation in Neural Systems, 6:469-505, 1995.
-
(1995)
Network: Computation in Neural Systems
, vol.6
, pp. 469-505
-
-
Mackay, D.J.C.1
-
25
-
-
71149119964
-
Online dictionary learning for sparse coding
-
New York, NY, USA, ACM
-
J. Mairal, F. Bach, J. Ponce, and G. Sapiro. Online dictionary learning for sparse coding. In Proceedings of the 26th Annual International Conference on Machine Learning (ICML2009), pages 689-696, New York, NY, USA, 2009. ACM.
-
(2009)
Proceedings of the 26th Annual International Conference on Machine Learning (ICML2009)
, pp. 689-696
-
-
Mairal, J.1
Bach, F.2
Ponce, J.3
Sapiro, G.4
-
26
-
-
2942534096
-
Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes
-
J. Pittman, E. Huang, H. Dressman, C. F. Horng, S. H. Cheng, M. H. Tsou, C M. Chen, A. Bild, E. S. Iversen, A. T. Huang, J. R. Nevins, and M. West. Integrated modeling of clinical and gene expression information for personalized prediction of disease outcomes. Proceedings of the National Academy of Sciences, 101:8431-8436, 2004.
-
(2004)
Proceedings of the National Academy of Sciences
, vol.101
, pp. 8431-8436
-
-
Pittman, J.1
Huang, E.2
Dressman, H.3
Horng, C.F.4
Cheng, S.H.5
Tsou, M.H.6
Chen, C.M.7
Bild, A.8
Iversen, E.S.9
Huang, A.T.10
Nevins, J.R.11
West, M.12
-
27
-
-
77953559148
-
The infinite hierarchical factor regression model
-
D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, editors Cambridge, MA, MIT Press
-
P. Rai and H. Daumé. The infinite hierarchical factor regression model. In D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou, editors, Advances in Neural Information Processing Systems 21, pages 1321-1328, Cambridge, MA, 2009. MIT Press.
-
(2009)
Advances in Neural Information Processing Systems
, vol.21
, pp. 1321-1328
-
-
Rai, P.1
Daumé, H.2
-
28
-
-
0032029288
-
Deterministic annealing em algorithm
-
N. Ueda and R. Nakano. Deterministic annealing EM algorithm. Neural Networks, 11:271-282, 1998.
-
(1998)
Neural Networks
, vol.11
, pp. 271-282
-
-
Ueda, N.1
Nakano, R.2
-
29
-
-
65749118363
-
Graphical models, exponential families, and variational inference
-
M.J. Wainwright and M.I. Jordan. Graphical models, exponential families, and variational inference. Foundations and Trends in Machine Learning, 1:1-305, 2008.
-
(2008)
Foundations and Trends in Machine Learning
, vol.1
, pp. 1-305
-
-
Wainwright, M.J.1
Jordan, M.I.2
-
30
-
-
62549117907
-
Bayesian factor regression modelling
-
Q. Wang, C.M. Carvalho, J.E. Lucas, and M. West. BFRM: Bayesian factor regression modelling. Bulletin of the International Society for Bayesian Analysis, 14(2):4-5, 2007.
-
(2007)
Bulletin of the International Society for Bayesian Analysis
, vol.14
, Issue.2
, pp. 4-5
-
-
Wang, Q.1
Carvalho, C.M.2
Lucas, J.E.3
West Bfrm, M.4
-
31
-
-
0242295767
-
Bayesian factor regression models in the "large p, small n" paradigm
-
J.M. Bernardo, M.J. Bayarri, J.O. Berger, A.P. Dawid, D. Heckerman, A.F.M. Smith, and M. West, editors, Oxford University Press
-
M. West. Bayesian factor regression models in the "large p, small n" paradigm. In J.M. Bernardo, M.J. Bayarri, J.O. Berger, A.P. Dawid, D. Heckerman, A.F.M. Smith, and M. West, editors, Bayesian Statistics 7, pages 723-732. Oxford University Press, 2003.
-
(2003)
Bayesian Statistics
, vol.7
, pp. 723-732
-
-
West, M.1
-
32
-
-
0035949684
-
Predicting the clinical status of human breast cancer utilizing gene expression profiles
-
M. West, C Blanchette, H. Dressman, E. Huang, S. Ishida, H. Zuzan R. Spang, J.R. Marks, and J.R. Nevins. Predicting the clinical status of human breast cancer utilizing gene expression profiles. Proceedings of the National Academy of Sciences, 98:11462-11467, 2001.
-
(2001)
Proceedings of the National Academy of Sciences
, vol.98
, pp. 11462-11467
-
-
West, M.1
Blanchette, C.2
Dressman, H.3
Huang, E.4
Ishida, S.5
Zuzan, H.6
Spang, R.7
Marks, J.R.8
Nevins, J.R.9
-
34
-
-
33745590867
-
An analytic tool for clustering, data visualization and module finder on gene expression profiles
-
R. Yoshida, T. Higuchi, S. Imoto, and S. Miyano. Arraycluster: an analytic tool for clustering, data visualization and module finder on gene expression profiles. Bioinformatics, 22(12): 1538-1539, 2006.
-
(2006)
Bioinformatics
, vol.22
, Issue.12
, pp. 1538-1539
-
-
Yoshida, R.1
Higuchi, T.2
Imoto, S.3
Miyano Arraycluster, S.4
-
35
-
-
33745309913
-
Sparse principal component analysis
-
H. Zou, T. Hastie, and R. Tibshirani. Sparse principal component analysis. Journal of Computational and Graphical Statistics, 15(2):265-286, 2006.
-
(2006)
Journal of Computational and Graphical Statistics
, vol.15
, Issue.2
, pp. 265-286
-
-
Zou, H.1
Hastie, T.2
Tibshirani, R.3
|