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AUTOMATICA
2007
13 years 7 months ago
2007
The sensor scheduling problem can be formulated as a controlled hidden Markov model and this paper solves the problem when the state, observation and action spaces are continuous....
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...
ESANN
2007
13 years 9 months ago
2007
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
TCSV
2008
13 years 7 months ago
2008
Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...