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ICML
2008
IEEE
16 years 4 months ago
An HDP-HMM for systems with state persistence
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,...
125
Voted
JMLR
2006
123views more  JMLR 2006»
15 years 3 months ago
Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies
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...
Fu Chang, Chin-Chin Lin, Chi-Jen Lu
135
Voted
ICML
2006
IEEE
16 years 4 months ago
Fast time series classification using numerosity reduction
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...
MICAI
2005
Springer
15 years 9 months ago
Knowledge and Reasoning Supported by Cognitive Maps
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...
Alejandro Peña Ayala, Humberto Sossa, Agust...
BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
15 years 6 months ago
Learning Scaling Coefficient in Possibilistic Latent Variable Algorithm from Complex Diagnosis Data
—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...
Zong-Xian Yin