-
1
-
-
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
-
2
-
-
1542367492
-
-
Preprint
-
P.L. Bartlett, M.I. Jordan and J.D. McAuliffe, Convexity, classification, and risk bounds, Preprint (2003).
-
(2003)
Convexity, Classification, and Risk Bounds
-
-
Bartlett, P.L.1
Jordan, M.I.2
McAuliffe, J.D.3
-
3
-
-
0026966646
-
A training algorithm for optimal margin classifiers
-
ACM, Pittsburgh
-
B.E. Boser, I. Guyon and V. Vapnik, A training algorithm for optimal margin classifiers, in: Proc. of the 5th Annual Workshop of Computational Learning Theory, Vol. 5 (ACM, Pittsburgh, 1992) pp. 144-152.
-
(1992)
Proc. of the 5th Annual Workshop of Computational Learning Theory
, vol.5
, pp. 144-152
-
-
Boser, B.E.1
Guyon, I.2
Vapnik, V.3
-
5
-
-
84879394399
-
Support vector machine soft margin classifiers: Error analysis
-
D. Chen, Q. Wu, Y. Ying and D.X. Zhou, Support vector machine soft margin classifiers: Error analysis, J. Mach. Learning Res. 5 (2004) 1143-1175.
-
(2004)
J. Mach. Learning Res.
, vol.5
, pp. 1143-1175
-
-
Chen, D.1
Wu, Q.2
Ying, Y.3
Zhou, D.X.4
-
6
-
-
34249753618
-
Support-vector networks
-
C. Cortes and V. Vapnik, Support-vector networks, Mach. Learning 20 (1995) 273-297.
-
(1995)
Mach. Learning
, vol.20
, pp. 273-297
-
-
Cortes, C.1
Vapnik, V.2
-
8
-
-
0036071370
-
On the mathematical foundations of learning
-
F. Cucker and S. Smale, On the mathematical foundations of learning, Bull. Amer. Math. Soc. 39 (2001) 1-49.
-
(2001)
Bull. Amer. Math. Soc.
, vol.39
, pp. 1-49
-
-
Cucker, F.1
Smale, S.2
-
9
-
-
0036436325
-
Best choices for regularization parameters in learning theory: On the biasvariance problem
-
F. Cucker and S. Smale, Best choices for regularization parameters in learning theory: On the biasvariance problem, Found. Comput. Math. 1 (2002) 413-428.
-
(2002)
Found. Comput. Math.
, vol.1
, pp. 413-428
-
-
Cucker, F.1
Smale, S.2
-
12
-
-
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
-
13
-
-
0037312471
-
A note on the universal approximation capability of support vector machines
-
B. Hammer and K. Gersmann, A note on the universal approximation capability of support vector machines, Neural Processing Lett. 17 (2003) 43-53.
-
(2003)
Neural Processing Lett.
, vol.17
, pp. 43-53
-
-
Hammer, B.1
Gersmann, K.2
-
14
-
-
0036258405
-
Support vector machines and the Bayes rule in classification
-
Y. Lin, Support vector machines and the Bayes rule in classification, Data Mining Knowledge Discovery 6 (2002) 259-275.
-
(2002)
Data Mining Knowledge Discovery
, vol.6
, pp. 259-275
-
-
Lin, Y.1
-
15
-
-
0000482137
-
On the relationship between generalization error, hypothesis complexity, and sample complexity for radial basis functions
-
P. Niyogi and F. Girosi, On the relationship between generalization error, hypothesis complexity, and sample complexity for radial basis functions, Neural Comput. 8 (1996) 819-842.
-
(1996)
Neural Comput.
, vol.8
, pp. 819-842
-
-
Niyogi, P.1
Girosi, F.2
-
18
-
-
0032166068
-
Structural risk minimization over data-dependent hierarchies
-
J. Shawe-Taylor, P.L. Bartlett, R.C. Williamson and M. Anthony, Structural risk minimization over data-dependent hierarchies, IEEE Trans. Inform. Theory 44 (1998) 1926-1940.
-
(1998)
IEEE Trans. Inform. Theory
, vol.44
, pp. 1926-1940
-
-
Shawe-Taylor, J.1
Bartlett, P.L.2
Williamson, R.C.3
Anthony, M.4
-
19
-
-
0037749769
-
Estimating the approximation error in learning theory
-
S. Smale and D.X. Zhou, Estimating the approximation error in learning theory, Anal. Appl. 1 (2003) 17-41.
-
(2003)
Anal. Appl.
, vol.1
, pp. 17-41
-
-
Smale, S.1
Zhou, D.X.2
-
20
-
-
3042850649
-
Shannon sampling and function reconstruction from point values
-
S. Smale and D.X. Zhou, Shannon sampling and function reconstruction from point values, Bull. Amer. Math. Soc. 41 (2004) 279-305.
-
(2004)
Bull. Amer. Math. Soc.
, vol.41
, pp. 279-305
-
-
Smale, S.1
Zhou, D.X.2
-
21
-
-
84876632679
-
Shannon sampling II. Connections to learning theory
-
(July) submitted by invitation
-
S. Smale and D.X. Zhou, Shannon sampling II. Connections to learning theory, Appl. Comput. Harmonic Anal. (July 2004) submitted by invitation.
-
(2004)
Appl. Comput. Harmonic Anal.
-
-
Smale, S.1
Zhou, D.X.2
-
22
-
-
0036749277
-
Support vector machines are universally consistent
-
I. Steinwart, Support vector machines are universally consistent, J. Complexity 18 (2002) 768-791.
-
(2002)
J. Complexity
, vol.18
, pp. 768-791
-
-
Steinwart, I.1
-
23
-
-
0010786475
-
On the influence of the kernel on the consistency of support vector machines
-
I. Steinwart, On the influence of the kernel on the consistency of support vector machines, J. Mach. Learning Res. 2 (2001) 67-73.
-
(2001)
J. Mach. Learning Res.
, vol.2
, pp. 67-73
-
-
Steinwart, I.1
-
24
-
-
3142725508
-
Optimal aggregation of classifiers in statistical learning
-
A.B. Tsybakov, Optimal aggregation of classifiers in statistical learning, Ann. Statist. 32 (2004) 135-166.
-
(2004)
Ann. Statist.
, vol.32
, pp. 135-166
-
-
Tsybakov, A.B.1
-
27
-
-
0001873883
-
Support vector machines, reproducing kernel Hubert spaces and the Randomized GACV
-
eds. Schölkopf, Burges and Smola (MIT Press, Cambridge, MA)
-
G. Wahba, Support vector machines, reproducing kernel Hubert spaces and the Randomized GACV, in: Advances in Kernel Methods - Support Vector Learning, eds. Schölkopf, Burges and Smola (MIT Press, Cambridge, MA, 1999) pp. 69-88.
-
(1999)
Advances in Kernel Methods - Support Vector Learning
, pp. 69-88
-
-
Wahba, G.1
-
30
-
-
33745676751
-
Support vector machine classifiers: Linear programming versus quadratic programming
-
in press
-
Q. Wu and D.X. Zhou, Support vector machine classifiers: Linear programming versus quadratic programming, Neural Computation, in press.
-
Neural Computation
-
-
Wu, Q.1
Zhou, D.X.2
-
31
-
-
4644257995
-
Statistical behavior and consistency of classification methods based on convex risk minimization
-
T. Zhang, Statistical behavior and consistency of classification methods based on convex risk minimization, Ann. Statist. 32 (2004) 56-85.
-
(2004)
Ann. Statist.
, vol.32
, pp. 56-85
-
-
Zhang, T.1
-
32
-
-
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
-
33
-
-
0038105204
-
Capacity of reproducing kernel spaces in learning theory
-
D.X. Zhou, Capacity of reproducing kernel spaces in learning theory, IEEE Trans. Inform. Theory 49 (2003) 1743-1752.
-
(2003)
IEEE Trans. Inform. Theory
, vol.49
, pp. 1743-1752
-
-
Zhou, D.X.1
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