Symbolic data analysis aims at generalizing some standard statistical data mining methods, such as those developed for classification tasks, to the case of symbolic objects (SOs). ...
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
This paper presents the person identification system developed at Athens Information Technology and its performance in the CLEAR 2007 evaluations. The system operates on the audiov...
Andreas Stergiou, Aristodemos Pnevmatikakis, Lazar...
Image classification or annotation is proved difficult for the computer algorithms. The Naive-Bayes Nearest Neighbor method is proposed to tackle the problem, and achieved the stat...
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...