43 search results - page 6 / 9 » Bayesian Nonparametric Inference of Switching Dynamic Linear... |
95
Voted
CVPR
1999
IEEE
15 years 11 months ago
1999
IEEE
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
100
Voted
KI
2010
Springer
14 years 7 months ago
2010
Springer
Recognizing human intentions is part of the decision process in many technical devices. In order to achieve natural interaction, the required estimation quality and the used comput...
80
Voted
ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
ISIPTA
2003
IEEE
15 years 2 months ago
2003
IEEE
Set-valued estimation offers a way to account for imprecise knowledge of the prior distribution of a Bayesian statistical inference problem. The set-valued Kalman filter, which p...
BIOINFORMATICS
2005
14 years 9 months ago
2005
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...