-
2
-
-
0042967689
-
Data-dependent margin-based generalization bounds for classification
-
ANTOS, A., KÉGL, B., LINDER, T. and LUGOSI, G. (2002). Data-dependent margin-based generalization bounds for classification. J. Mach. Learn. Res. 3 73-98.
-
(2002)
J. Mach. Learn. Res.
, vol.3
, pp. 73-98
-
-
Antos, A.1
Kégl, B.2
Linder, T.3
Lugosi, G.4
-
3
-
-
4944233194
-
Aggregated estimators and empirical complexity for least square regression
-
AUDIBERT, J.-Y. (2004). Aggregated estimators and empirical complexity for least square regression. Ann. Inst. H. Poincaré Probab. Statist. 40 685-736.
-
(2004)
Ann. Inst. H. Poincaré Probab. Statist.
, vol.40
, pp. 685-736
-
-
Audibert, J.-Y.1
-
4
-
-
0032028728
-
The sample complexity of pattern classification with neural networks: The size of the weights is more important than the size of the network
-
BARTLETT, P. (1998). The sample complexity of pattern classification with neural networks: The size of the weights is more important than the size of the network. IEEE Trans. Inform. Theory 44 525-536.
-
(1998)
IEEE Trans. Inform. Theory
, vol.44
, pp. 525-536
-
-
Bartlett, P.1
-
7
-
-
3042675892
-
On the rate of convergence of regularized boosting classifiers
-
BLANCHARD, G., LUGOSI, G. and VAYATIS, N. (2004). On the rate of convergence of regularized boosting classifiers. J. Mach. Learn. Res. 4 861-894.
-
(2004)
J. Mach. Learn. Res.
, vol.4
, pp. 861-894
-
-
Blanchard, G.1
Lugosi, G.2
Vayatis, N.3
-
8
-
-
26444452739
-
Some local measures of complexity of convex hulls and generalization bounds
-
Springer, Berlin
-
BOUSQUET, O., KOLTCHINSKII, V. and PANCHENKO, D. (2002). Some local measures of complexity of convex hulls and generalization bounds. Computational Learning Theory. Lecture Notes in Artificial Intelligence 2375 59-73. Springer, Berlin.
-
(2002)
Computational Learning Theory. Lecture Notes in Artificial Intelligence
, vol.2375
, pp. 59-73
-
-
Bousquet, O.1
Koltchinskii, V.2
Panchenko, D.3
-
9
-
-
0030211964
-
Bagging predictors
-
BREIMAN, L. (1996). Bagging predictors. Machine Learning 24 123-140.
-
(1996)
Machine Learning
, vol.24
, pp. 123-140
-
-
Breiman, L.1
-
10
-
-
0346786584
-
Arcing classifiers
-
BREIMAN, L. (1998). Arcing classifiers (with discussion). Ann. Statist. 26 801-849.
-
(1998)
Ann. Statist.
, vol.26
, pp. 801-849
-
-
Breiman, L.1
-
11
-
-
0000275022
-
Prediction games and arcing algorithms
-
BREIMAN, L. (1999). Prediction games and arcing algorithms. Neural Computation 11 1493-1517.
-
(1999)
Neural Computation
, vol.11
, pp. 1493-1517
-
-
Breiman, L.1
-
14
-
-
0000996139
-
Sphere packing numbers for subsets of the Boolean n-cube with bounded Vapnik-Chervonenkis dimension
-
HAUSSLER, D. (1995). Sphere packing numbers for subsets of the Boolean n-cube with bounded Vapnik-Chervonenkis dimension. J. Combin. Theory Ser. A 69 217-232.
-
(1995)
J. Combin. Theory Ser. A
, vol.69
, pp. 217-232
-
-
Haussler, D.1
-
15
-
-
26444545593
-
Process consistency for AdaBoost
-
JIANG, W. (2004). Process consistency for AdaBoost. Ann. Statist. 32 13-29.
-
(2004)
Ann. Statist.
, vol.32
, pp. 13-29
-
-
Jiang, W.1
-
16
-
-
0141425582
-
Bounds on margin distributions in learning problems
-
KOLTCHINSKII, V. (2003). Bounds on margin distributions in learning problems. Ann. Inst. H. Poincaré Probab. Statist. 39 943-978.
-
(2003)
Ann. Inst. H. Poincaré Probab. Statist.
, vol.39
, pp. 943-978
-
-
Koltchinskii, V.1
-
18
-
-
0001166808
-
Rademacher processes and bounding the risk of function learning
-
(E. Giné, D. Mason and J. Wellner, eds.). Birkhäuser, Boston
-
KOLTCHINSKII, V. and PANCHENKO, D. (2000). Rademacher processes and bounding the risk of function learning. In High Dimensional Probability II (E. Giné, D. Mason and J. Wellner, eds.) 443-459. Birkhäuser, Boston.
-
(2000)
High Dimensional Probability II
, pp. 443-459
-
-
Koltchinskii, V.1
Panchenko, D.2
-
19
-
-
0036104545
-
Empirical margin distributions and bounding the generalization error of combined classifiers
-
KOLTCHINSKII, V. and PANCHENKO, D. (2002). Empirical margin distributions and bounding the generalization error of combined classifiers. Ann. Statist. 30 1-50.
-
(2002)
Ann. Statist.
, vol.30
, pp. 1-50
-
-
Koltchinskii, V.1
Panchenko, D.2
-
21
-
-
0037274322
-
Bounding the generalization error of convex combinations of classifiers: Balancing the dimensionality and the margins
-
KOLTCHINSKII, V., PANCHENKO, D. and LOZANO, F. (2003). Bounding the generalization error of convex combinations of classifiers: Balancing the dimensionality and the margins. Ann. Appl. Probab. 13 213-252.
-
(2003)
Ann. Appl. Probab.
, vol.13
, pp. 213-252
-
-
Koltchinskii, V.1
Panchenko, D.2
Lozano, F.3
-
22
-
-
9444269961
-
On the Bayes-risk consistency of regularized boosting methods
-
LUGOSI, G. and VAYATIS, N. (2004). On the Bayes-risk consistency of regularized boosting methods. Ann. Statist. 32 30-55.
-
(2004)
Ann. Statist.
, vol.32
, pp. 30-55
-
-
Lugosi, G.1
Vayatis, N.2
-
24
-
-
0347979483
-
A note on Talagrand's concentration inequality
-
PANCHENKO, D. (2001). A note on Talagrand's concentration inequality. Electron. Comm. Probab. 6 55-65.
-
(2001)
Electron. Comm. Probab.
, vol.6
, pp. 55-65
-
-
Panchenko, D.1
-
25
-
-
0347349284
-
Some extensions of an inequality of Vapnik and Chervonenkis
-
PANCHENKO, D. (2002). Some extensions of an inequality of Vapnik and Chervonenkis. Electron. Comm. Probab. 7 55-65.
-
(2002)
Electron. Comm. Probab.
, vol.7
, pp. 55-65
-
-
Panchenko, D.1
-
26
-
-
0347593390
-
Symmetrization approach to concentration inequalities for empirical processes
-
PANCHENKO, D. (2003). Symmetrization approach to concentration inequalities for empirical processes. Ann. Probab. 31 2068-2081.
-
(2003)
Ann. Probab.
, vol.31
, pp. 2068-2081
-
-
Panchenko, D.1
-
27
-
-
0003345901
-
Remarques sur un résultat non publié de B. Maurey
-
École Polytechnic, Palaiseau. Exp.
-
PISIER, G. (1981). Remarques sur un résultat non publié de B. Maurey. In Seminar on Functional Analysis, 1980-1981, École Polytechnic, Palaiseau. Exp. no. V, 13 pp.
-
(1981)
Seminar on Functional Analysis, 1980-1981
, vol.5
-
-
Pisier, G.1
-
28
-
-
0032280519
-
Boosting the margin: A new explanation for the effectiveness of voting methods
-
SCHAPIRE, R., FREUND, Y., BARTLETT, P. and LEE, W. S. (1998). Boosting the margin: A new explanation for the effectiveness of voting methods. Ann. Statist. 26 1651-1686.
-
(1998)
Ann. Statist.
, vol.26
, pp. 1651-1686
-
-
Schapire, R.1
Freund, Y.2
Bartlett, P.3
Lee, W.S.4
-
29
-
-
0033281701
-
Improved boosting algorithms using confidence-rated predictions
-
SCHAPIRE, R. and SINGER, Y. (1999). Improved boosting algorithms using confidence-rated predictions. Machine Learning 37 297-336.
-
(1999)
Machine Learning
, vol.37
, pp. 297-336
-
-
Schapire, R.1
Singer, Y.2
-
30
-
-
4644354708
-
Sparseness of support vector machines
-
STEINWART, I. (2004). Sparseness of support vector machines. J. Mach. Learn. Res. 4 1071-1105.
-
(2004)
J. Mach. Learn. Res.
, vol.4
, pp. 1071-1105
-
-
Steinwart, I.1
-
33
-
-
4644257995
-
Statistical behavior and consistency of classification methods based on convex risk minimization
-
ZHANG, T. (2004). Statistical behavior and consistency of classification methods based on convex risk minimization. Ann. Statist. 32 56-85.
-
(2004)
Ann. Statist.
, vol.32
, pp. 56-85
-
-
Zhang, T.1
-
34
-
-
26444493144
-
Boosting with early stopping: Convergence and consistency
-
ZHANG, T. and YU, B. (2005). Boosting with early stopping: Convergence and consistency. Ann. Statist. 33 1538-1579.
-
(2005)
Ann. Statist.
, vol.33
, pp. 1538-1579
-
-
Zhang, T.1
Yu, B.2
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