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164
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EMMCVPR
2001
Springer
15 years 10 months ago
2001
Springer
Hidden Markov Models (HMMs) are an useful and widely utilized approach to the modeling of data sequences. One of the problems related to this technique is finding the optimal stru...
210
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SDM
2008
SIAM
15 years 7 months ago
2008
SIAM
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
162
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CVPR
2007
IEEE
16 years 8 months ago
2007
IEEE
Class syntax can be used to 1) model temporal or locational evolvement of class labels of feature observation sequences, 2) correct classification errors of static classifiers if ...
181
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WWW
2008
ACM
16 years 7 months ago
2008
ACM
In this paper, we propose a novel unsupervised approach to query segmentation, an important task in Web search. We use a generative query model to recover a query's underlyin...
151
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GECCO
2005
Springer
15 years 11 months ago
2005
Springer
Typical applications of evolutionary optimization in static environments involve the approximation of the extrema of functions. For dynamic environments, the interest is not to lo...