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» A Bayesian Approach to Tackling Hard Computational Problems
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EWC
2010
91views more  EWC 2010»
13 years 6 months ago
Multiobjective global surrogate modeling, dealing with the 5-percent problem
When dealing with computationally expensive simulation codes or process measurement data, surrogate modeling methods are firmly established as facilitators for design space explor...
Dirk Gorissen, Ivo Couckuyt, Eric Laermans, Tom Dh...
COCO
2006
Springer
93views Algorithms» more  COCO 2006»
13 years 11 months ago
Making Hard Problems Harder
We consider a general approach to the hoary problem of (im)proving circuit lower bounds. We define notions of hardness condensing and hardness extraction, in analogy to the corres...
Joshua Buresh-Oppenheim, Rahul Santhanam
FLAIRS
2003
13 years 8 months ago
An Extension of the Differential Approach for Bayesian Network Inference to Dynamic Bayesian Networks
We extend the differential approach to inference in Bayesian networks (BNs) (Darwiche, 2000) to handle specific problems that arise in the context of dynamic Bayesian networks (D...
Boris Brandherm
ICCV
2009
IEEE
15 years 13 days ago
Bayesian selection of scaling laws for motion modeling in images
Based on scaling laws describing the statistical structure of turbulent motion across scales, we propose a multiscale and non-parametric regularizer for optic-flow estimation. R...
Patrick H´eas, Etienne M´emin, Dominique Heitz, ...
ENC
2005
IEEE
14 years 1 months ago
Hard Problem Generation for MKP
We developed generators that produce challenging MKP instances. Our approaches uses independently exponential distributions over a wide range to generate the constraint coefficien...
Maria A. Osorio, Germn Cuaya