147 search results - page 13 / 30 » Learning Multi-linear Representations of Distributions for E... |
FTML
2008
13 years 7 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
13 years 7 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...
NIPS
2000
13 years 8 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
14 years 9 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...
IPPS
1999
IEEE
13 years 11 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 ...