Asymptotic Properties of Neural Network Sieve Estimators

[author] Grenander, UlfU. (1981). Abstract Inference. Wily, New York

1981

Earlier work this paper cites.

[author] Wu, Chien-FuC.-F. (1981). Asymptotic theory of nonlinear least squares estimation. The Annals of Statistics 501–513

1981

Earlier work this paper cites.

[author] Alexander, Kenneth SK. S. (1984). Probability inequalities for empirical processes and a law of the iterated logarithm. The Annals of Probability 1041–1067

1984

Earlier work this paper cites.

[author] Hornik, KurtK., Stinchcombe, MaxwellM. and White, HalbertH. (1989). Multilayer feedforward networks are universal approximators. Neural networks 2 359–366

1989

Earlier work this paper cites.

[author] White, HalbertH. (1989). Learning in artificial neural networks: A statistical perspective. Neural computation 1 425–464

1989

Earlier work this paper cites.

[author] White, HalbertH. (1990). Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings. Neural networks 3 535–549

1990

Earlier work this paper cites.

[author] White, HalbertH. and Wooldridge, JJ. (1991). Some results on sieve estimation with dependent observations. In Nonparametric and Semiparametric Methods in Economics (W. A.W. A. Barnett, J.J. Powell and G.G. Tauchen, eds.) 459–493. Cambridge University Press New York

1991

Earlier work this paper cites.

[author] Shen, XiaotongX. and Wong, Wing HungW. H. (1994). Convergence rate of sieve estimates. The Annals of Statistics 580–615

1994

Earlier work this paper cites.

[author] Fukumizu, KenjiK. (1996). A regularity condition of the information matrix of a multilayer perceptron network. Neural networks 9 871–879

1996

Earlier work this paper cites.

[author] Makovoz, YulyY. (1996). Random approximants and neural networks. Journal of Approximation Theory 85 98–109

1996

Cited alongside, same era.

[author] van der Vaart, Aad WA. W. and Wellner, Jon AJ. A. (1996). Weak convergence and empirical processes. Springer

1996

Cited alongside, same era.

[author] Shen, XiaotongX. (1997). On methods of sieves and penalization. The Annals of Statistics 2555–2591

1997

Cited alongside, same era.

[author] Chen, XiaohongX. and Shen, XiaotongX. (1998). Sieve extremum estimates for weakly dependent data. Econometrica 289–314

1998

Cited alongside, same era.

[author] Vapnik, VladimirV. (1998). Statistical learning theory. 1998 3. Wiley, New York

1998

Cited alongside, same era.

[author] Liu, XinX. and Shao, YongzhaoY. (2003). Asymptotics for likelihood ratio tests under loss of identifiability. The Annals of Statistics 31 807–832

2003

Later among the works it cites.

[author] Mendelson, ShaharS. (2003). A few notes on statistical learning theory. In Advanced lectures on machine learning 1–40. Springer

2003

Later among the works it cites.

[author] Boyd, StephenS. and Mutapcic, AlmirA. (2008). Subgradient Methods (notes for EE364B Winter 2006-07, Stanford University)

2006

Later among the works it cites.

[author] Zhu, HongtuH. and Zhang, HepingH. (2006). Asymptotics for estimation and testing procedures under loss of identifiability. Journal of Multivariate Analysis 97 19–45

2006

Later among the works it cites.

[author] Anthony, MartinM. and Bartlett, Peter LP. L. (2009). Neural network learning: Theoretical foundations. cambridge university press