The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
In this paper, we propose a number of adaptive prototype learning (APL) algorithms. They employ the same algorithmic scheme to determine the number and location of prototypes, but...
Many algorithms have been proposed for the problem of time series classification. However, it is clear that one-nearest-neighbor with Dynamic Time Warping (DTW) distance is except...
Xiaopeng Xi, Eamonn J. Keogh, Christian R. Shelton...
A powerful and useful approach for modeling knowledge and qualitative reasoning is the Cognitive Map. The background of Cognitive Maps is the research about learning environments c...
—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...