Clustering time-series data poses problems, which do not exist in traditional clustering in Euclidean space. Specifically, cluster prototype needs to be calculated, where common s...
Conventional clustering techniques provide a static snapshot of each vector's commitment to every group. With additive datasets, however, existing methods may not be sufficie...
Kernel logistic regression models, like their linear counterparts, can be trained using the efficient iteratively reweighted least-squares (IRWLS) algorithm. This approach suggest...
This paper explores the issues involved in using symbolic metric algorithms for automatic speech recognition (ASR), via a structural representation of speech. This representation ...
In this work, two new techniques for non-linear feature extraction are presented. In these techniques, new features are obtained as radial projections of the original measurements...