Halbert White - RankMe

26 papers B 1Journal 20Unranked 5

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Testing a constant mean function using functional regression. Neural Comput. Appl. Jin Seo Cho, Meng Huang, Halbert White
2012	J	`jnl`	Causality, Conditional Independence, and Graphical Separation in Settable Systems. Neural Comput. Karim Chalak, Halbert White
2012	J	`jnl`	Higher-Order Approximations for Testing Neglected Nonlinearity. Neural Comput. Halbert White, Jin Seo Cho
2011	—	`conf`	Linking Granger Causality and the Pearl Causal Model with Settable Systems. NIPS Mini-Symposium on Causality in Time Series Halbert White, Karim Chalak, Xun Lu
2011	J	`jnl`	Revisiting Tests for Neglected Nonlinearity Using Artificial Neural Networks. Neural Comput. Jin Seo Cho, Isao Ishida, Halbert White
2011	J	`jnl`	Testing correct model specification using extreme learning machines. Neurocomputing Jin Seo Cho, Halbert White
2009	J	`jnl`	Settable Systems: An Extension of Pearl's Causal Model with Optimization, Equilibrium, and Learning. J. Mach. Learn. Res. Halbert White, Karim Chalak
1999	J	`jnl`	Improved Rates and Asymptotic Normality for Nonparametric Neural Network Estimators. IEEE Trans. Inf. Theory Xiaohong Chen, Halbert White
1996	J	`jnl`	Experience with selecting exemplars from clean data. Neural Networks Mark Plutowski, Garrison W. Cottrell, Halbert White
1995	J	`jnl`	Bootstrapping confidence intervals for clinical input variable effects in a network trained to identify the presence of acute myocardial infarction. Neural Comput. William G. Baxt, Halbert White
1995	J	`jnl`	Regularized neural networks: some convergence rate results. Neural Comput. Valentina Corradi, Halbert White
1995	J	`jnl`	Sup-norm approximation bounds for networks through probabilistic methods. IEEE Trans. Inf. Theory Joseph E. Yukich, Maxwell B. Stinchcombe, Halbert White
1994	J	`jnl`	A Convergence Result for Learning in Recurrent Neural Networks. Neural Comput. Chung-Ming Kuan, Kurt Hornik, Halbert White
1994	J	`jnl`	Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives. Neural Comput. Kurt Hornik, Maxwell B. Stinchcombe, Halbert White, Peter Auer
1993	—	`conf`	Cross-Validation Estimates ISME. NIPS Mark Plutowski, Shinichi Sakata, Halbert White
1993	—	`conf`	Learning Mackey-Glass from 25 Examples, Plus or Minus 2. NIPS Mark Plutowski, Garrison W. Cottrell, Halbert White
1993	J	`jnl`	Letters to the editor. Neural Networks Kurt Hornik, Maxwell B. Stinchcombe, Halbert White
1993	J	`jnl`	Selecting concise training sets from clean data. IEEE Trans. Neural Networks Mark Plutowski, Halbert White
1992	J	`jnl`	On learning the derivatives of an unknown mapping with multilayer feedforward networks. Neural Networks A. Ronald Gallant, Halbert White
1990	B	`conf`	Approximating and learning unknown mappings using multilayer feedforward networks with bounded weights. IJCNN Maxwell B. Stinchcombe, Halbert White
1990	J	`jnl`	Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings. Neural Networks Halbert White
1990	J	`jnl`	Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks. Neural Networks Kurt Hornik, Maxwell B. Stinchcombe, Halbert White
1989	J	`jnl`	Learning in Artificial Neural Networks: A Statistical Perspective. Neural Comput. Halbert White
1989	J	`jnl`	Multilayer feedforward networks are universal approximators. Neural Networks Kurt Hornik, Maxwell B. Stinchcombe, Halbert White
1988	—	`conf`	Economic prediction using neural networks: the case of IBM daily stock returns. ICNN Halbert White
1988	—	`conf`	There exists a neural network that does not make avoidable mistakes. ICNN A. Ronald Gallant, Halbert White