-
1
-
-
0031176507
-
Scale-sensitive dimensions, uniform convergence, and learnability
-
N. Alon, S. Ben-David, N. Cesa-Bianchi, and D. Haussler, Scale-sensitive dimensions, uniform convergence, and learnability, J. ACM 44 (1997), 615-631.
-
(1997)
J. ACM
, vol.44
, pp. 615-631
-
-
Alon, N.1
Ben-David, S.2
Cesa-Bianchi, N.3
Haussler, D.4
-
2
-
-
5844297152
-
Theory of reproducing kernels
-
N. Aronszajn, Theory of reproducing kernels, Trans. Amer. Math. Soc. 68 (1950), 337-404.
-
(1950)
Trans. Amer. Math. Soc.
, vol.68
, pp. 337-404
-
-
Aronszajn, N.1
-
3
-
-
0036643049
-
Model selection and error estimation
-
P. Bartlett, S. Boucheron, and G. Lugosi, Model selection and error estimation, Machine Learn-ing 48 (2002), 85-113.
-
(2002)
Machine Learn-ing
, vol.48
, pp. 85-113
-
-
Bartlett, P.1
Boucheron, S.2
Lugosi, G.3
-
6
-
-
0036436325
-
Best choices for regularization parameters in learning theory: On the bias-variance problem
-
F. Cucker and S. Smale, Best choices for regularization parameters in learning theory: On the bias-variance problem, Found. Comput. Math. 2 (2002), 413-428.
-
(2002)
Found. Comput. Math.
, vol.2
, pp. 413-428
-
-
Cucker, F.1
Smale, S.2
-
7
-
-
0036071370
-
On the mathematical foundations of learning
-
F. Cucker and S. Smale, On the mathematical foundations of learning, Bull. Amer. Math. Soc. (N.S.) 39 (2002), 1-49.
-
(2002)
Bull. Amer. Math. Soc. (N.S.)
, vol.39
, pp. 1-49
-
-
Cucker, F.1
Smale, S.2
-
8
-
-
0004019773
-
-
Springer-Verlag, New York
-
L. Devroye, L. Györfi, and G. Lugosi, A Probabilistic Theory of Pattern Recognition, Springer-Verlag, New York, 1996.
-
(1996)
A Probabilistic Theory of Pattern Recognition
-
-
Devroye, L.1
Györfi, L.2
Lugosi, G.3
-
10
-
-
0034419669
-
Regularization networks and support vector machines
-
T. Evgeniou, M. Pontil, and T. Poggio, Regularization networks and support vector machines, Adv. Comput. Math. 13 (2000), 1-50.
-
(2000)
Adv. Comput. Math.
, vol.13
, pp. 1-50
-
-
Evgeniou, T.1
Pontil, M.2
Poggio, T.3
-
11
-
-
0001219859
-
Regularization theory and neural networks architectures
-
F. Girosi, M. Jones, and T. Poggio, Regularization theory and neural networks architectures, Neural Comput. 7 (1995), 219-269.
-
(1995)
Neural Comput.
, vol.7
, pp. 219-269
-
-
Girosi, F.1
Jones, M.2
Poggio, T.3
-
12
-
-
0003684449
-
-
Springer-Verlag, New York
-
T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, Springer-Verlag, New York, 2001.
-
(2001)
The Elements of Statistical Learning
-
-
Hastie, T.1
Tibshirani, R.2
Friedman, J.3
-
13
-
-
0001035413
-
On the method of bounded differences
-
1989 (Norwich, 1989), Cambridge University Press, Cambridge
-
C. McDiarmid, On the method of bounded differences, in Surveys in Combinatorics, 1989 (Norwich, 1989), Cambridge University Press, Cambridge, 1989, pp. 148-188.
-
(1989)
Surveys in Combinatorics
, pp. 148-188
-
-
McDiarmid, C.1
-
14
-
-
35248851077
-
A few notes on statistical learning theory
-
(S. Mendelson and A. Smola, eds.), Springer-Verlag
-
S. Mendelson, A few notes on statistical learning theory, in Advanced Lectures in Machine Learning (S. Mendelson and A. Smola, eds.), Springer-Verlag, 2003, pp. 1-40.
-
(2003)
Advanced Lectures in Machine Learning
, pp. 1-40
-
-
Mendelson, S.1
-
15
-
-
0033480745
-
Generalization bounds for function approximation from scattered noisy data
-
P. Niyogi and F. Girosi, Generalization bounds for function approximation from scattered noisy data, Adv. Comput. Math. 10 (1999), 51-80.
-
(1999)
Adv. Comput. Math.
, vol.10
, pp. 51-80
-
-
Niyogi, P.1
Girosi, F.2
-
16
-
-
0025490985
-
Networks for approximation and learning
-
T. Poggio and F. Girosi, Networks for approximation and learning, in Proceedings of the IEEE, Vol. 78, 1990, pp. 1481-1497.
-
(1990)
Proceedings of the IEEE
, vol.78
, pp. 1481-1497
-
-
Poggio, T.1
Girosi, F.2
-
17
-
-
1842420581
-
General conditions for predictivity in learning theory
-
T. Poggio, R. Rifkin, S. Mukherjee, and P. Niyogi, General conditions for predictivity in learning theory, Nature 428 (2004), 419-422.
-
(2004)
Nature
, vol.428
, pp. 419-422
-
-
Poggio, T.1
Rifkin, R.2
Mukherjee, S.3
Niyogi, P.4
-
18
-
-
1842733197
-
Are loss functions all the same?
-
L. Rosasco, E. De Vito, A. Caponnetto, M. Piana, and A. Verri, Are loss functions all the same?, Neural Comput. 16 (2004), 1063-1076.
-
(2004)
Neural Comput.
, vol.16
, pp. 1063-1076
-
-
Rosasco, L.1
De Vito, E.2
Caponnetto, A.3
Piana, M.4
Verri, A.5
-
19
-
-
0037749769
-
Estimating the approximation error in learning theory
-
S. Smale and D.-X. Zhou, Estimating the approximation error in learning theory, Anal. Appl. (Singap.) 1 (2003), 17-41.
-
(2003)
Anal. Appl. (Singap.)
, vol.1
, pp. 17-41
-
-
Smale, S.1
Zhou, D.-X.2
-
20
-
-
84898974114
-
Consistency of support vector machines and other regularized kernel machines
-
University of Jena, Department of Mathematics and Computer Science
-
I. Steinwart, Consistency of support vector machines and other regularized kernel machines, Technical Report 02-03, University of Jena, Department of Mathematics and Computer Science, 2002.
-
(2002)
Technical Report
, vol.2
, Issue.3
-
-
Steinwart, I.1
-
23
-
-
0042879446
-
Leave-one-out bounds for kernel methods
-
T. Zhang, Leave-one-out bounds for kernel methods, Neural Comput. 15 (2003), 1397-1437.
-
(2003)
Neural Comput.
, vol.15
, pp. 1397-1437
-
-
Zhang, T.1
-
24
-
-
0036748375
-
The covering number in learning theory
-
D.-X. Zhou, The covering number in learning theory, J. Complexity 18 (2002), 739-767.
-
(2002)
J. Complexity
, vol.18
, pp. 739-767
-
-
Zhou, D.-X.1
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