Halbert White - researchr alias

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Viewing Publication 1 - 26 from 26

2023

Testing a constant mean function using functional regressionJin Seo Cho, Meng Huang, Halbert White. nca, 35(29):21915-21934, October 2023. [doi]

2012

Causality, Conditional Independence, and Graphical Separation in Settable SystemsKarim Chalak, Halbert White. neco, 24(7):1611-1668, 2012. [doi]

Higher-Order Approximations for Testing Neglected NonlinearityHalbert White, Jin Seo Cho. neco, 24(1):273-287, 2012. [doi]

2011

Revisiting Tests for Neglected Nonlinearity Using Artificial Neural NetworksJin Seo Cho, Isao Ishida, Halbert White. neco, 23(5):1133-1186, 2011. [doi]

Testing correct model specification using extreme learning machinesJin Seo Cho, Halbert White. ijon, 74(16):2552-2565, 2011. [doi]

Linking Granger Causality and the Pearl Causal Model with Settable SystemsHalbert White, Karim Chalak, Xun Lu. jmlr, 12:1-29, 2011. [doi]

2009

Settable Systems: An Extension of Pearl s Causal Model with Optimization, Equilibrium, and LearningHalbert White, Karim Chalak. jmlr, 10:1759-1799, 2009. [doi]

1999

Improved Rates and Asymptotic Normality for Nonparametric Neural Network EstimatorsXiaohong Chen, Halbert White. TIT, 45(2):682-691, 1999.

1996

Experience with selecting exemplars from clean dataMark Plutowski, Garrison W. Cottrell, Halbert White. NN, 9(2):273-294, 1996. [doi]

1995

Bootstrapping confidence intervals for clinical input variable effects in a network trained to identify the presence of acute myocardial infarctionWilliam G. Baxt, Halbert White. neco, 7(3):624-638, 1995.

Regularized neural networks: some convergence rate resultsValentina Corradi, Halbert White. neco, 7(6):1225-1244, 1995. [doi]

Sup-norm approximation bounds for networks through probabilistic methodsJoseph E. Yukich, Maxwell B. Stinchcombe, Halbert White. TIT, 41(4):1021-1027, 1995.

1994

Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their DerivativesKurt Hornik, Maxwell B. Stinchcombe, Halbert White, Peter Auer. neco, 6(6):1262-1275, 1994. [doi]

A Convergence Result for Learning in Recurrent Neural NetworksChung-Ming Kuan, Kurt Hornik, Halbert White. neco, 6(3):420-440, 1994. [doi]

1993

1992

On learning the derivatives of an unknown mapping with multilayer feedforward networksA. Ronald Gallant, Halbert White. NN, 5(1):129-138, 1992. [doi]

1990

Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networksKurt Hornik, Maxwell B. Stinchcombe, Halbert White. NN, 3(5):551-560, 1990. [doi]

Approximating and learning unknown mappings using multilayer feedforward networks with bounded weightsMaxwell B. Stinchcombe, Halbert White. ijcnn 1990: 7-16 [doi]

Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappingsHalbert White. NN, 3(5):535-549, 1990. [doi]

1989

Multilayer feedforward networks are universal approximatorsKurt Hornik, Maxwell B. Stinchcombe, Halbert White. NN, 2(5):359-366, 1989. [doi]

Learning in Artificial Neural Networks: A Statistical PerspectiveHalbert White. neco, 1(4):425-464, 1989. [doi]

1988

There exists a neural network that does not make avoidable mistakesA. Ronald Gallant, Halbert White. icnn 1988: 657-664 [doi]

Economic prediction using neural networks: the case of IBM daily stock returnsHalbert White. icnn 1988: 451-458 [doi]

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