311 search results - page 31 / 63 » Learning Probabilistic Models of Link Structure |
131
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ESOP
2011
Springer
14 years 3 months ago
2011
Springer
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
102
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CORR
2012
Springer
13 years 7 months ago
2012
Springer
We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...
105
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ISBI
2008
IEEE
16 years 15 days ago
2008
IEEE
In this paper we present a learning based method for vessel segmentation in angiographic videos. Vessel Segmentation is an important task in medical imaging and has been investiga...
ICDM
2007
IEEE
15 years 6 months ago
2007
IEEE
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
103
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CIKM
2008
Springer
15 years 1 months ago
2008
Springer
We propose a novel probabilistic method based on the Hidden Markov Model (HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed...