This paper deals with the interaction between progressive model adaptation and score normalization strategies which are used for reducing the variation in likelihood ratio scores ...
Abstract--Plenty of methods have been proposed in order to discover latent variables (features) in data sets. Such approaches include the principal component analysis (PCA), indepe...
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
The analysis of reading times can provide insights into the processes that underlie language comprehension, with longer reading times indicating greater cognitive load. There is e...
Jeff Mitchell, Mirella Lapata, Vera Demberg, Frank...
Rotation Forest is a recently proposed method for building classifier ensembles using independently trained decision trees. It was found to be more accurate than bagging, AdaBoost...