-
2
-
-
41549101939
-
Model selection through sparse maximum likelihood estimation for multivariate gaussian or binary data
-
Banerjee, O.; Ghaoui, L. E.; and d'Aspremont, A. 2008. Model selection through sparse maximum likelihood estimation for multivariate gaussian or binary data. Journal of Machine Learning Research 9:485-516.
-
(2008)
Journal of Machine Learning Research
, vol.9
, pp. 485-516
-
-
Banerjee, O.1
Ghaoui, L.E.2
D'Aspremont, A.3
-
3
-
-
45849134070
-
Sparse inverse covariance estimation with the graphical lasso
-
Friedman, J.; Hastie, T.; and Tibshirani, R. 2008. Sparse inverse covariance estimation with the graphical lasso. J. Biostatis-lies 9(3):432-44l.
-
(2008)
J. Biostatis-lies
, vol.9
, Issue.3
-
-
Friedman, J.1
Hastie, T.2
Tibshirani, R.3
-
4
-
-
66549109770
-
Estimation of sparse binary pairwise markov networks using pseudo-likelihoods
-
Höfling, H., and Tibshirani, R. 2009. Estimation of sparse binary pairwise markov networks using pseudo-likelihoods. J. Mach. Learn. Res. 10:883-906.
-
(2009)
J. Mach. Learn. Res.
, vol.10
, pp. 883-906
-
-
Höfling, H.1
Tibshirani, R.2
-
5
-
-
0003641246
-
On the effective implementation of the iterative proportional fitting procedure
-
Jirouśek, R., and Pr̂euĉil, S. 1995. On the effective implementation of the iterative proportional fitting procedure. Comput. Stat. Data Anal. 19(2): 177-189.
-
(1995)
Comput. Stat. Data Anal.
, vol.19
, Issue.2
, pp. 177-189
-
-
Jirouśek, R.1
Pr̂euĉil, S.2
-
8
-
-
70049111780
-
1-regularization
-
Schölkopf, B.; Platt, J.; and Hoffman, T, eds., Cambridge, MA: MIT Press.
-
1 In Schölkopf, B.; Platt, J.; and Hoffman, T, eds., Advances in Neural Information Processing Systems 19. Cambridge, MA: MIT Press. 817-824.
-
(2007)
Advances in Neural Information Processing Systems
, vol.19
, pp. 817-824
-
-
Lee, S.-I.1
Ganapathi, V.2
Koller, D.3
-
9
-
-
70049104366
-
Sparse gaussian graphical models with unknown block structure
-
Danyluk, A. P.; Bottou, L.; and Littman, M. L., eds., ICML, ACM
-
Marlin, B. M., and Murphy, K. P. 2009. Sparse gaussian graphical models with unknown block structure. In Danyluk, A. P.; Bottou, L.; and Littman, M. L., eds., ICML, volume 382 of ACM International Conference Proceeding Series, 89. ACM.
-
(2009)
ACM International Conference Proceeding Series
, vol.382
, pp. 89
-
-
Marlin, B.M.1
Murphy, K.P.2
-
10
-
-
33747163541
-
High-dimensional graphs and variable selection with the lasso
-
Meinshausen, N., and Bühlmann, P. 2006. High-dimensional graphs and variable selection with the lasso. Annals of Statistics 34(3): 1436-1462.
-
(2006)
Annals of Statistics
, vol.34
, Issue.3
, pp. 1436-1462
-
-
Meinshausen, N.1
Bühlmann, P.2
-
11
-
-
38049184884
-
Modeling highway traffic volumes
-
ECML, Springer
-
Singliar, T, and Hauskrecht, M. 2007. Modeling highway traffic volumes. In ECML, volume 4701 of Lecture Notes in Computer Science, 732-739. Springer.
-
(2007)
Lecture Notes in Computer Science
, vol.4701
, pp. 732-739
-
-
Singliar, T.1
Hauskrecht, M.2
-
12
-
-
84864034065
-
1 -regularized logistic regression
-
Schölkopf, B.; Platt, J.; and Hoffman, T, eds., Cambridge, MA: MIT Press.
-
1 -regularized logistic regression. In Schölkopf, B.; Platt, J.; and Hoffman, T, eds., Advances in Neural Information Processing Systems 19. Cambridge, MA: MIT Press. 1465-1472.
-
(2007)
Advances in Neural Information Processing Systems
, vol.19
, pp. 1465-1472
-
-
Wainwright, M.J.1
Ravikumar, P.2
Lafferty, J.D.3
|