147 search results - page 13 / 30 » Learning Multi-linear Representations of Distributions for E... |
80
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FTML
2008
14 years 9 months ago
2008
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
IJAR
2006
14 years 9 months ago
2006
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
110
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NIPS
2000
14 years 11 months ago
2000
Jensen's inequality is a powerful mathematical tool and one of the workhorses in statistical learning. Its applications therein include the EM algorithm, Bayesian estimation ...
ICCV
2007
IEEE
15 years 11 months ago
2007
IEEE
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
83
Voted
IPPS
1999
IEEE
15 years 2 months ago
1999
IEEE
This paper explains how efficient support for semiregular distributions can be incorporated in a uniform compilation framework for hybrid applications. The key focus of this work ...