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UAI
2004
14 years 11 months ago
Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters
A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
Peter Hooper
IJCV
2000
93views more  IJCV 2000»
14 years 9 months ago
How Optimal Depth Cue Integration Depends on the Task
Bayesian parameter estimation can be used to generate statistically optimal solutions to the problem of cue integration. However, the complexity and dimensionality of these solutio...
Paul R. Schrater, Daniel Kersten
EMNLP
2011
13 years 9 months ago
Unsupervised Dependency Parsing without Gold Part-of-Speech Tags
We show that categories induced by unsupervised word clustering can surpass the performance of gold part-of-speech tags in dependency grammar induction. Unlike classic clustering ...
Valentin I. Spitkovsky, Hiyan Alshawi, Angel X. Ch...
CVPR
2006
IEEE
15 years 12 months ago
Learning Patch Dependencies for Improved Pose Mismatched Face Verification
Most pose robust face verification algorithms, which employ 2D appearance, rely heavily on statistics gathered from offline databases containing ample facial appearance variation ...
Simon Lucey, Tsuhan Chen
RECOMB
2003
Springer
15 years 10 months ago
Modeling dependencies in protein-DNA binding sites
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...