95 search results - page 12 / 19 » Learning Markov Logic Networks Using Structural Motifs |
NAACL
2007
14 years 11 months ago
2007
We propose a high-performance cascaded hybrid model for Chinese NER. Firstly, we use Boosting, a standard and theoretically wellfounded machine learning method to combine a set of...
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...
85
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NN
1997
Springer
15 years 1 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
84
Voted
ML
2008
ACM
14 years 9 months ago
2008
ACM
Abstract. Recently, there has been an increasing interest in directed probabilistic logical models and a variety of languages for describing such models has been proposed. Although...
100
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ECAI
2010
Springer
14 years 7 months ago
2010
Springer
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...