273 search results - page 15 / 55 » Learning the Structure of Deep Sparse Graphical Models |
131
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JMLR
2010
14 years 8 months ago
2010
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
109
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TMI
1998
15 years 1 months ago
1998
Abstract— This paper reports a novel method for fully automated segmentation that is based on description of shape and its variation using point distribution models (PDM’s). An...
119
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GIS
2008
ACM
15 years 2 months ago
2008
ACM
Bintrees based on longest edge bisection and hierarchies of diamonds are popular multiresolution techniques on regularly sampled terrain datasets. In this work, we consider sparse...
127
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CORR
2012
Springer
13 years 9 months ago
2012
Springer
We show that the log-likelihood of several probabilistic graphical models is Lipschitz continuous with respect to the p-norm of the parameters. We discuss several implications ...
139
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KDD
2009
ACM
15 years 6 months ago
2009
ACM
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...