-
1
-
-
14344252374
-
Multiple kernels learning, conic duality, and the SMO algorithm
-
F.R. Bach, G.R.G. Lanckriet and M.I. Jordan. Multiple kernels learning, conic duality, and the SMO algorithm. In Proceedings of the Twenty-first International Conference on Machine Learning (ICML 2004), pages 6-13, 2004.
-
(2004)
Proceedings of the Twenty-first International Conference on Machine Learning (ICML 2004)
, pp. 6-13
-
-
Bach, F.R.1
Lanckriet, G.R.G.2
Jordan, M.I.3
-
3
-
-
77950244328
-
Model based compressed sensing
-
R. Baraniuk, V. Cevher, M.F. Duarte, C. Hedge. Model based compressed sensing. IEEE Trans, on Information Theory, 56:1982-2001, 2010.
-
(2010)
IEEE Trans, on Information Theory
, vol.56
, pp. 1982-2001
-
-
Baraniuk, R.1
Cevher, V.2
Duarte, M.F.3
Hedge, C.4
-
4
-
-
0038453192
-
Rademacher and Gaussian complexities: Risk bounds and structural results
-
P.L. Bartlett and S. Mendelson. Rademacher and Gaussian Complexities: Risk Bounds and Structural Results. Journal of Machine Learning Research, 3:463-482, 2002.
-
(2002)
Journal of Machine Learning Research
, vol.3
, pp. 463-482
-
-
Bartlett, P.L.1
Mendelson, S.2
-
6
-
-
62549127689
-
Elastic-net regularization in learning theory
-
C. De Mol, E. De Vito, L. Rosasco. Elastic-net regularization in learning theory. Journal of Complexity, 25(2):201-230, 2009.
-
(2009)
Journal of Complexity
, vol.25
, Issue.2
, pp. 201-230
-
-
De Mol, C.1
De Vito, E.2
Rosasco, L.3
-
7
-
-
84947403595
-
Probability inequalities for sums of bounded random variables
-
W. Hoeffding, Probability inequalities for sums of bounded random variables, Journal of the American Statistical Association, 58:13-30, 1963.
-
(1963)
Journal of the American Statistical Association
, vol.58
, pp. 13-30
-
-
Hoeffding, W.1
-
12
-
-
79955848223
-
Norm multiple kernel learning
-
M. Kloft, U. Brefeld, S. Sonnenburg, A. Zien. Norm multiple kernel learning. Journal of Machine Learning Research, 12:953-997, 2011.
-
(2011)
Journal of Machine Learning Research
, vol.12
, pp. 953-997
-
-
Kloft, M.1
Brefeld, U.2
Sonnenburg, S.3
Zien, A.4
-
13
-
-
0036104545
-
Empirical margin distributions and bounding the generalization error of combined classifiers
-
V. Koltchinskii and D. Panchenko, Empirical margin distributions and bounding the generalization error of combined classifiers, Annals of Statistics, 30(1): 1-50, 2002. (Pubitemid 37095367)
-
(2002)
Annals of Statistics
, vol.30
, Issue.1
, pp. 1-50
-
-
Koltchinskii, V.1
Panchenko, D.2
-
14
-
-
8844278523
-
Learning the kernel matrix with semi-definite programming
-
G.R.G. Lanckriet, N. Cristianini, PL. Bartlett, L. El Ghaoui, M.I. Jordan. Learning the kernel matrix with semi-definite programming. Journal of Machine Learning Research, 5:27-72, 2004.
-
(2004)
Journal of Machine Learning Research
, vol.5
, pp. 27-72
-
-
Lanckriet, G.R.G.1
Cristianini, N.2
Bartlett, P.L.3
El Ghaoui, L.4
Jordan, M.I.5
-
16
-
-
84855412474
-
Oracle inequalities and optimal inference under group sparsity
-
K. Lounici, M. Pontil, A.B. Tsybakov and S. van de Geer. Oracle inequalities and optimal inference under group sparsity. Annals of Statistics, 39(4):2164-2204, 2011.
-
(2011)
Annals of Statistics
, vol.39
, Issue.4
, pp. 2164-2204
-
-
Lounici, K.1
Pontil, M.2
Tsybakov, A.B.3
Geer De S.Van4
-
18
-
-
73949083829
-
High-dimensional additive modeling
-
L. Meier, S.A. van de Geer, and P. Bühlmann. High-dimensional additive modeling. Annals of Statistics, 37(6B):3779-3821, 2009.
-
(2009)
Annals of Statistics
, vol.37
, Issue.6 B
, pp. 3779-3821
-
-
Meier, L.1
Geer De Van, S.A.2
Bühlmann, P.3
-
19
-
-
3142691501
-
Generalization error bounds for Bayesian mixture algorithms
-
R. Meir and T. Zhang. Generalization error bounds for Bayesian mixture algorithms. Journal of Machine Learning Research, 4:839-860, 2003.
-
(2003)
Journal of Machine Learning Research
, vol.4
, pp. 839-860
-
-
Meir, R.1
Zhang, T.2
-
22
-
-
33847662483
-
Feature space perspectives for learning the kernel
-
DOI 10.1007/s10994-006-0679-0, Special Issue on Learning Theory
-
C.A. Micchelli and M. Pontil. Feature space perspectives for learning the kernel. Machine Learning, 66:297-319,2007. (Pubitemid 46360616)
-
(2007)
Machine Learning
, vol.66
, Issue.2-3
, pp. 297-319
-
-
Micchelli, C.A.1
Pontil, M.2
-
24
-
-
46749151407
-
Weighted Lasso in graphical Gaussian modeling for large gene network estimation based on microarray data
-
T. Shimamura, S. Imoto, R. Yamaguchi and S. Miyano. Weighted Lasso in graphical Gaussian modeling for large gene network estimation based on microarray data. Genome Informatics, 19:142-153, 2007.
-
(2007)
Genome Informatics
, vol.19
, pp. 142-153
-
-
Shimamura, T.1
Imoto, S.2
Yamaguchi, R.3
Miyano, S.4
-
27
-
-
69949155103
-
Grouped and hierarchical model selection through composite absolute penalties
-
P. Zhao and G. Rocha and B. Yu. Grouped and hierarchical model selection through composite absolute penalties. Annals of Statistics, 37(6A):3468-3497, 2009.
-
(2009)
Annals of Statistics
, vol.37
, Issue.6 A
, pp. 3468-3497
-
-
Zhao, P.1
Rocha, G.2
Yu, B.3
|