Density Estimation with Imprecise Kernels: Application to Classification

At the preceding GREC [Barbu 2005] , we have proposed to use a “bag of symbols” formalism (similar to the bag of words approach) for the indexing of a graphical document

In our approach, we benefit from these advantages to reduce the resolution of the video by using a multiscale/multiresolution decomposition, to define a new algorithm which decomposes

Combining Imprecise Probability Masses with Maximal Co- herent Subsets: Application to Ensemble Classification.. Soft Methods in Probability and Statistics, Oct

Experiments show that including an imprecise component in the Gaussian discriminant analysis produces reasonably cautious predictions, in the sense that the number of

After introducing the model and its inference process based on Smet’s generalized Bayes theorem (GBT), we specify some possible methods to learn its parameters, based on the

We also show that the use of belief functions allows us to combine the information contained into different input data derived from the whole spectrum data, and that it is an

PREDICTING WHEN TO LAUGH WITH STRUCTURED CLASSIFICATION Bilal Piot 1 , Olivier Pietquin 2 , Matthieu Geist 1.. 1 SUPELEC IMS-MaLIS research group and UMI 2958 (GeorgiaTech

At the preceding GREC [Barbu 2005] , we have proposed to use a “bag of symbols” formalism (similar to the bag of words approach) for the indexing of a graphical document