-
3
-
-
0027599793
-
Universal approximation bounds for superpositions of a sigmoidal function
-
Barron, A. R. (1993). Universal approximation bounds for superpositions of a sigmoidal function. IEEE Trans. on Information Theory, 39, 930-945.
-
(1993)
IEEE Trans. on Information Theory
, vol.39
, pp. 930-945
-
-
Barron, A.R.1
-
5
-
-
0036071370
-
On the mathematical foundations of learning
-
Cucker, F., & Smale, S. (2002). On the mathematical foundations of learning. Bulletin of AMS, 39, 1-49.
-
(2002)
Bulletin of AMS
, vol.39
, pp. 1-49
-
-
Cucker, F.1
Smale, S.2
-
6
-
-
0024861871
-
Approximation by superpositions of a sigmoidal function
-
Cybenko, G. (1989). Approximation by superpositions of a sigmoidal function. Mathematics of Control and Signals Systems, 2, 303-314.
-
(1989)
Mathematics of Control and Signals Systems
, vol.2
, pp. 303-314
-
-
Cybenko, G.1
-
8
-
-
0024880831
-
Multi-layer feedforward networks are universal approximators
-
Hornik, K., Stinchcombe, M., & White, H. (1989). Multi-layer feedforward networks are universal approximators. Neural Networks, 2, 359-366.
-
(1989)
Neural Networks
, vol.2
, pp. 359-366
-
-
Hornik, K.1
Stinchcombe, M.2
White, H.3
-
9
-
-
0025799121
-
Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory
-
Ito, Y. (1991). Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory. Neural Networks, 4, 385-394.
-
(1991)
Neural Networks
, vol.4
, pp. 385-394
-
-
Ito, Y.1
-
10
-
-
0001929506
-
Finite mapping by neural networks and truth functions
-
Ito, Y. (1992). Finite mapping by neural networks and truth functions. Math. Scientist, 17, 69-77.
-
(1992)
Math. Scientist
, vol.17
, pp. 69-77
-
-
Ito, Y.1
-
11
-
-
0000796112
-
A simple lemma on greedy approximation in Hilbert space and convergence rates for projection pursuit regression and neural network training
-
Jones, L. K. (1992). A simple lemma on greedy approximation in Hilbert space and convergence rates for projection pursuit regression and neural network training. Annals of Statistics, 20, 608-613.
-
(1992)
Annals of Statistics
, vol.20
, pp. 608-613
-
-
Jones, L.K.1
-
12
-
-
0008185462
-
Quasiorthogonal dimension of Euclidean spaces
-
Kainen, P. C., & Kůrková, V. (1993). Quasiorthogonal dimension of Euclidean spaces. Applied Math. Letters, 6, 7-10.
-
(1993)
Applied Math. Letters
, vol.6
, pp. 7-10
-
-
Kainen, P.C.1
Kůrková, V.2
-
13
-
-
0344993943
-
Approximation by neural networks is not continuous
-
Kainen, P. C., Kůrková, V., & Vogt, A. (1999). Approximation by neural networks is not continuous. Neurocomputing, 29, 47-56.
-
(1999)
Neurocomputing
, vol.29
, pp. 47-56
-
-
Kainen, P.C.1
Kůrková, V.2
Vogt, A.3
-
14
-
-
0008241587
-
Geometry and topology of continuous best and near best approximations
-
Kainen, P. C., Kůrková, V., & Vogt, A. (2000a). Geometry and topology of continuous best and near best approximations. Journal of Approximation Theory, 105, 252-262.
-
(2000)
Journal of Approximation Theory
, vol.105
, pp. 252-262
-
-
Kainen, P.C.1
Kůrková, V.2
Vogt, A.3
-
15
-
-
18744387645
-
An integral formula for Heaviside neural networks
-
Kainen, P. C., Kůrková, V., & Vogt, A. (2000b). An integral formula for Heaviside neural networks. Neural Network World, 10, 313-320.
-
(2000)
Neural Network World
, vol.10
, pp. 313-320
-
-
Kainen, P.C.1
Kůrková, V.2
Vogt, A.3
-
16
-
-
0038009873
-
Best approximation by linear combinations of characteristic functions of half-spaces
-
Kainen, P. C., Kůrková, V., & Vogt, A. (2003). Best approximation by linear combinations of characteristic functions of half-spaces. Journal of Approximation Theory, 122, 151-159.
-
(2003)
Journal of Approximation Theory
, vol.122
, pp. 151-159
-
-
Kainen, P.C.1
Kůrková, V.2
Vogt, A.3
-
17
-
-
37749004818
-
Integral combinations of Heavisides. Submitted
-
ICS-966. Available online at
-
Kainen, P. C., Kůrková, V., & Vogt, A. (2006). Integral combinations of Heavisides. Submitted, Research report ICS-966. Available online at http://www.es.cas.cz/research/publications.shtml.
-
(2006)
Research report
-
-
Kainen, P.C.1
Kůrková, V.2
Vogt, A.3
-
18
-
-
34447641642
-
A Sobolev-type upper bound for rates of approximation by linear combinations of plane waves
-
Kainen, P. C., Kůrková, V., & Vogt, A. (2007). A Sobolev-type upper bound for rates of approximation by linear combinations of plane waves. Journal of Approximation Theory, 147, 1-10.
-
(2007)
Journal of Approximation Theory
, vol.147
, pp. 1-10
-
-
Kainen, P.C.1
Kůrková, V.2
Vogt, A.3
-
20
-
-
4043167595
-
High-dimensional approximation and optimization by neural networks
-
J. Suykens, G. Horvath, S. Basu, C. Micchelli, & J. Vandewalle Eds, Amsterdam: IOS Press
-
Kůrková, V. (2003). High-dimensional approximation and optimization by neural networks. In J. Suykens, G. Horvath, S. Basu, C. Micchelli, & J. Vandewalle (Eds.), Advances in learning theory: Methods, models and applications (pp. 69-88). Amsterdam: IOS Press.
-
(2003)
Advances in learning theory: Methods, models and applications
, pp. 69-88
-
-
Kůrková, V.1
-
21
-
-
37749014010
-
Minimization of empirical error functional over perceptron networks
-
B. Ribeiro, R. F. Albrecht, A. Dobnikar, D. W. Pearson, & N. C. Steele Eds, Berlin: Springer-Verlag
-
Kůrková, V. (2005). Minimization of empirical error functional over perceptron networks. In B. Ribeiro, R. F. Albrecht, A. Dobnikar, D. W. Pearson, & N. C. Steele (Eds.), Adaptive and natural computing algorithms (pp. 46-49). Berlin: Springer-Verlag.
-
(2005)
Adaptive and natural computing algorithms
, pp. 46-49
-
-
Kůrková, V.1
-
22
-
-
0343118761
-
Estimates of the number of hidden units and variation with respect to half-spaces
-
Kůrková, V., Kainen, P. C., & Kreinovich, V. (1997). Estimates of the number of hidden units and variation with respect to half-spaces. Neural Networks, 10, 1061-1068.
-
(1997)
Neural Networks
, vol.10
, pp. 1061-1068
-
-
Kůrková, V.1
Kainen, P.C.2
Kreinovich, V.3
-
23
-
-
0032096332
-
Representations and rates of approximation of real-valued Boolean functions by neural networks
-
Kůrková, V., Savický, P., & Hlaváč ková, K. (1998). Representations and rates of approximation of real-valued Boolean functions by neural networks. Neural Networks, 11, 651-659.
-
(1998)
Neural Networks
, vol.11
, pp. 651-659
-
-
Kůrková, V.1
Savický, P.2
Hlaváč ková, K.3
-
24
-
-
0027262895
-
Multilayer feedforward networks with a non-polynomial activation can approximate any function
-
Leshno, M., Lin, V. Y., Pinkus, A., & Schocken, S. (1993). Multilayer feedforward networks with a non-polynomial activation can approximate any function. Neural Networks, 6, 861-867.
-
(1993)
Neural Networks
, vol.6
, pp. 861-867
-
-
Leshno, M.1
Lin, V.Y.2
Pinkus, A.3
Schocken, S.4
-
25
-
-
0030119952
-
Random approximants and neural networks
-
Makovoz, Y. (1996). Random approximants and neural networks. Journal of Approximation Theory, 85, 98-109.
-
(1996)
Journal of Approximation Theory
, vol.85
, pp. 98-109
-
-
Makovoz, Y.1
-
26
-
-
0001574595
-
Uniform approximation by neural networks
-
Makovoz, Y. (1998). Uniform approximation by neural networks. Journal of Approximation Theory, 95, 215-228.
-
(1998)
Journal of Approximation Theory
, vol.95
, pp. 215-228
-
-
Makovoz, Y.1
-
28
-
-
37449032880
-
Approximation theory of the MPL model in neural networks
-
Pinkus, A. (1998). Approximation theory of the MPL model in neural networks. Acta Numerica, 8, 277-283.
-
(1998)
Acta Numerica
, vol.8
, pp. 277-283
-
-
Pinkus, A.1
-
29
-
-
0008977715
-
Remarques sur un résultat non publié de B. Maurey
-
Palaiseau, France: Ecole Polytechnique, Centre de Mathématiques
-
Pisier, G. (1981). Remarques sur un résultat non publié de B. Maurey. In Séminaire d'Analyse Fonctionnelle 1980-81. Palaiseau, France: Ecole Polytechnique, Centre de Mathématiques.
-
(1981)
Séminaire d'Analyse Fonctionnelle 1980-81
-
-
Pisier, G.1
-
30
-
-
37749041414
-
On the bent Boolean functions that are symmetric
-
Savický, P. (1994). On the bent Boolean functions that are symmetric. European Journal of Combinatorics, 15, 145-168.
-
(1994)
European Journal of Combinatorics
, vol.15
, pp. 145-168
-
-
Savický, P.1
-
35
-
-
0004146423
-
Backpropagation: Basics and new developments
-
M. Arbib Ed, Cambridge, MA: MIT Press
-
Werbos, P. J. (1985). Backpropagation: Basics and new developments. In M. Arbib (Ed.), The handbook of brain theory and neural networks (pp. 134-139). Cambridge, MA: MIT Press.
-
(1985)
The handbook of brain theory and neural networks
, pp. 134-139
-
-
Werbos, P.J.1
|