91 search results - page 15 / 19 » Bayesian learning of joint distributions of objects |
133
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SODA
2001
ACM
15 years 5 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
144
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CVPR
2008
IEEE
16 years 6 months ago
2008
IEEE
We propose a novel approach for activity analysis in multiple synchronized but uncalibrated static camera views. We assume that the topology of camera views is unknown and quite a...
153
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AAAI
2008
15 years 6 months ago
2008
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
179
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PAMI
2011
14 years 11 months ago
2011
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
178
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CVPR
2005
IEEE
15 years 6 months ago
2005
IEEE
The segmentation of anatomical structures has been traditionally formulated as a perceptual grouping task, and solved through clustering and variational approaches. However, such ...