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» Modeling Classification and Inference Learning
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DAGM
2010
Springer
13 years 9 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen
JMLR
2010
192views more  JMLR 2010»
13 years 3 months ago
Inducing Tree-Substitution Grammars
Inducing a grammar from text has proven to be a notoriously challenging learning task despite decades of research. The primary reason for its difficulty is that in order to induce...
Trevor Cohn, Phil Blunsom, Sharon Goldwater
CLEF
2010
Springer
13 years 9 months ago
UPMC/LIP6 at ImageCLEFannotation 2010
In this paper, we present the LIP6 annotation models for the ImageCLEFannotation 2010 task. We study two methods to train and merge the results of different classifiers in order to...
Ali Fakeri-Tabrizi, Sabrina Tollari, Nicolas Usuni...
CVPR
2004
IEEE
14 years 10 months ago
Model-Based Motion Clustering Using Boosted Mixture Modeling
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...
Vladimir Pavlovic
AAAI
2006
13 years 9 months ago
Automatically Labeling the Inputs and Outputs of Web Services
Information integration systems combine data from multiple heterogeneous Web services to answer complex user queries, provided a user has semantically modeled the service first. T...
Kristina Lerman, Anon Plangprasopchok, Craig A. Kn...