37 search results - page 3 / 8 » Parametric Kernels for Sequence Data Analysis |
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
An intuitive approach to utilizing unlabeled data in kernel-based classification algorithms is to simply treat unknown labels as additional optimization variables. For marginbased...
AUSAI
2008
Springer
13 years 10 months ago
2008
Springer
Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent,...
CSDA
2008
13 years 8 months ago
2008
An m-sample semiparametric model in which the ratio of m - 1 probability density functions with respect to the mth is of a known parametric form without reference to any parametri...
NIPS
2008
13 years 10 months ago
2008
We introduce a kernel-based method for change-point analysis within a sequence of temporal observations. Change-point analysis of an unlabelled sample of observations consists in,...
CVPR
2004
IEEE
14 years 10 months ago
2004
IEEE
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...