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NN
2006
Springer
163views Neural Networks» more  NN 2006»
13 years 7 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
CSB
2005
IEEE
166views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Artificial Neural Networks to Predict Daylily Hybrids
Artificial Neural Networks (ANN) were employed to predict daylily (Hemerocalli spp.) hybrids from known characteristics of parents used in hybridization. Features such as height, ...
Ramana M. Gosukonda, Masoud Naghedolfeizi, Johnny ...
VTC
2006
IEEE
110views Communications» more  VTC 2006»
14 years 1 months ago
Recurrent Neural Network Based Narrowband Channel Prediction
Abstract—In this contribution, the application of fully connected recurrent neural networks (FCRNNs) is investigated in the context of narrowband channel prediction. Three differ...
Wei Liu, Lie-Liang Yang, Lajos Hanzo
ML
2008
ACM
222views Machine Learning» more  ML 2008»
13 years 7 months ago
Boosted Bayesian network classifiers
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
ML
1998
ACM
153views Machine Learning» more  ML 1998»
13 years 7 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun