Halbert White

Meng Huang

Neural Comput. Appl., October, 2023

2012

Higher-Order Approximations for Testing Neglected Nonlinearity.

[BibT_eX]

[DOI]

Neural Comput., 2012

Causality, Conditional Independence, and Graphical Separation in Settable Systems.

[BibT_eX]

[DOI]

Karim Chalak

Neural Comput., 2012

2011

Revisiting Tests for Neglected Nonlinearity Using Artificial Neural Networks.

[BibT_eX]

[DOI]

Isao Ishida

Neural Comput., 2011

Linking Granger Causality and the Pearl Causal Model with Settable Systems.

[BibT_eX]

[DOI]

Karim Chalak

Xun Lu

Proceedings of the Neural Information Processing Systems (NIPS) Mini-Symposium on Causality in Time Series, 2011

Testing correct model specification using extreme learning machines.

[BibT_eX]

[DOI]

Neurocomputing, 2011

2009

Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning.

[BibT_eX]

[DOI]

Karim Chalak

J. Mach. Learn. Res., 2009

2001

Statistical inference, the bootstrap, and neural-network modeling with application to foreign exchange rates.

[BibT_eX]

[DOI]

Halbert L. White

Jeffrey S. Racine

IEEE Trans. Neural Networks, 2001

Introduction to the special issue on neural networks in financial engineering.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks, 2001

1999

Improved Rates and Asymptotic Normality for Nonparametric Neural Network Estimators.

[BibT_eX]

[DOI]

Xiaohong Chen

IEEE Trans. Inf. Theory, 1999

1996

Experience with selecting exemplars from clean data.

[BibT_eX]

[DOI]

Garrison W. Cottrell

Neural Networks, 1996

1995

Sup-norm approximation bounds for networks through probabilistic methods.

[BibT_eX]

[DOI]

Joseph E. Yukich

IEEE Trans. Inf. Theory, 1995

Regularized neural networks: some convergence rate results.

[BibT_eX]

[DOI]

Valentina Corradi

Neural Comput., 1995

Bootstrapping confidence intervals for clinical input variable effects in a network trained to identify the presence of acute myocardial infarction.

[BibT_eX]

[DOI]

William G. Baxt

Neural Comput., 1995

1994

A Convergence Result for Learning in Recurrent Neural Networks.

[BibT_eX]

[DOI]

Chung-Ming Kuan

Neural Comput., 1994

Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives.

[BibT_eX]

[DOI]

Peter Auer

Neural Comput., 1994

1993

Selecting concise training sets from clean data.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks, 1993

Letters to the editor.

[BibT_eX]

[DOI]

Neural Networks, 1993

Cross-Validation Estimates ISME.

[BibT_eX]

[DOI]

Shinichi Sakata

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Learning Mackey-Glass from 25 Examples, Plus or Minus 2.

[BibT_eX]

[DOI]

Garrison W. Cottrell

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992

On learning the derivatives of an unknown mapping with multilayer feedforward networks.

[BibT_eX]

[DOI]

A. Ronald Gallant

Neural Networks, 1992

1990

Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings.

[BibT_eX]

[DOI]

Neural Networks, 1990

Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks.

[BibT_eX]

[DOI]

Neural Networks, 1990

Approximating and learning unknown mappings using multilayer feedforward networks with bounded weights.

[BibT_eX]

[DOI]

Proceedings of the IJCNN 1990, 1990

1989

Multilayer feedforward networks are universal approximators.

[BibT_eX]

[DOI]

Neural Networks, 1989

Learning in Artificial Neural Networks: A Statistical Perspective.

[BibT_eX]

[DOI]

Neural Comput., 1989

1988

Economic prediction using neural networks: the case of IBM daily stock returns.

[BibT_eX]

[DOI]

Proceedings of International Conference on Neural Networks (ICNN'88), 1988

There exists a neural network that does not make avoidable mistakes.

[BibT_eX]

[DOI]

A. Ronald Gallant