Radial basis function networks in nonparametric classification and function learning
暂无分享,去创建一个
[1] Donald F. Specht,et al. Probabilistic neural networks , 1990, Neural Networks.
[2] A. Barron. Approximation and Estimation Bounds for Artificial Neural Networks , 1991, COLT '91.
[3] 中澤 真,et al. Devroye, L., Gyorfi, L. and Lugosi, G. : A Probabilistic Theory of Pattern Recognition, Springer (1996). , 1997 .
[4] Adam Krzyzak,et al. Radial Basis Function Networks and Complexity Regularization in Function Learning , 2022 .
[5] David W. Scott,et al. Multivariate Density Estimation: Theory, Practice, and Visualization , 1992, Wiley Series in Probability and Statistics.
[6] Jooyoung Park,et al. Universal Approximation Using Radial-Basis-Function Networks , 1991, Neural Computation.
[7] A. Krzyżak,et al. On Radial Basis Function Net and Kernel Regression: Approximation Ability, Convergence Rate and Receptive Field Size , 1993, Proceedings. IEEE International Symposium on Information Theory.
[8] J. Simonoff. Smoothing Methods in Statistics , 1998 .
[9] John Moody,et al. Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.
[10] László Györfi,et al. A Probabilistic Theory of Pattern Recognition , 1996, Stochastic Modelling and Applied Probability.
[11] Adam Krzyzak,et al. Nonparametric estimation and classification using radial basis function nets and empirical risk minimization , 1996, IEEE Trans. Neural Networks.
[12] Andrew R. Barron,et al. Universal approximation bounds for superpositions of a sigmoidal function , 1993, IEEE Trans. Inf. Theory.
[13] Tomaso A. Poggio,et al. Regularization Theory and Neural Networks Architectures , 1995, Neural Computation.
[14] Federico Girosi,et al. On the Relationship between Generalization Error, Hypothesis Complexity, and Sample Complexity for Radial Basis Functions , 1996, Neural Computation.
[15] Kurt Hornik,et al. FEED FORWARD NETWORKS ARE UNIVERSAL APPROXIMATORS , 1989 .
[16] John Fox,et al. What Is Nonparametric Regression , 2000 .
[17] Jooyoung Park,et al. Approximation and Radial-Basis-Function Networks , 1993, Neural Computation.
[18] W. Härdle. Applied Nonparametric Regression , 1991 .
[19] Adam Krzyzak,et al. On radial basis function nets and kernel regression: Statistical consistency, convergence rates, and receptive field size , 1994, Neural Networks.
[20] Richard J. Mammone,et al. Artificial neural networks for speech and vision , 1994 .