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AAAI
2011
12 years 7 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
ICDE
2011
IEEE
207views Database» more  ICDE 2011»
12 years 11 months ago
Monte Carlo query processing of uncertain multidimensional array data
— Array database systems are architected for scientific and engineering applications. In these applications, the value of a cell is often imprecise and uncertain. There are at le...
Tingjian Ge, David Grabiner, Stanley B. Zdonik
ICML
2009
IEEE
14 years 8 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
CORR
2006
Springer
104views Education» more  CORR 2006»
13 years 7 months ago
Loop corrections for approximate inference
We propose a method to improve approximate inference methods by correcting for the influence of loops in the graphical model. The method is a generalization and alternative implem...
Joris M. Mooij, Bert Kappen
PG
1999
IEEE
13 years 11 months ago
Boundary Determination for Trivariate Solids
The trivariate tensor-product B-spline solid is a direct extension of the B-spline patch and has been shown to be useful in the creation and visualization of free-form geometric s...
Kenneth I. Joy, Mark A. Duchaineau