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AUTOMATICA
2005
155views more  AUTOMATICA 2005»
13 years 8 months ago
Identification of MIMO Hammerstein models using least squares support vector machines
This paper studies a method for the identification of Hammerstein models based on Least Squares Support Vector Machines (LS-SVMs). The technique allows for the determination of th...
Ivan Goethals, Kristiaan Pelckmans, Johan A. K. Su...
FINTAL
2006
14 years 2 days ago
Incorporating External Information in Bayesian Classifiers Via Linear Feature Transformations
Naive Bayes classifier is a frequently used method in various natural language processing tasks. Inspired by a modified version of the method called the flexible Bayes classifier, ...
Tapio Pahikkala, Jorma Boberg, Aleksandr Myllä...
PAMI
2006
147views more  PAMI 2006»
13 years 8 months ago
Bayesian Gaussian Process Classification with the EM-EP Algorithm
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
Hyun-Chul Kim, Zoubin Ghahramani
ICML
2008
IEEE
14 years 9 months ago
A reproducing kernel Hilbert space framework for pairwise time series distances
A good distance measure for time series needs to properly incorporate the temporal structure, and should be applicable to sequences with unequal lengths. In this paper, we propose...
Zhengdong Lu, Todd K. Leen, Yonghong Huang, Deniz ...
MLCW
2005
Springer
14 years 1 months ago
Estimating Predictive Variances with Kernel Ridge Regression
In many regression tasks, in addition to an accurate estimate of the conditional mean of the target distribution, an indication of the predictive uncertainty is also required. Ther...
Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chap...