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» The Computational Structure of Progress Conditions
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CVPR
2010
IEEE
15 years 5 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
GG
2008
Springer
14 years 10 months ago
High-Level Programs and Program Conditions
High-level conditions are well-suited for expressing structural properties. They can describe the precondition and the postcondition for a high-level program, but they cannot descr...
Karl Azab, Annegret Habel
NAR
2006
98views more  NAR 2006»
14 years 9 months ago
oGNM: online computation of structural dynamics using the Gaussian Network Model
An assessment of the equilibrium dynamics of biomolecular systems, and in particular their most cooperativefluctuationsaccessibleundernativestate conditions, is a first step towar...
Lee-Wei Yang, A. J. Rader, Xiong Liu, Christopher ...
CVPR
2009
IEEE
16 years 4 months ago
Capturing Multiple Illumination Conditions using Time and Color Multiplexing
Many vision and graphics problems such as relighting, structured light scanning and photometric stereo, need im- ages of a scene under a number of different illumination conditi...
Bert De Decker (Hasselt University), Jan Kautz (Un...
JMLR
2010
102views more  JMLR 2010»
14 years 4 months ago
Efficient Algorithms for Conditional Independence Inference
The topic of the paper is computer testing of (probabilistic) conditional independence (CI) implications by an algebraic method of structural imsets. The basic idea is to transfor...
Remco R. Bouckaert, Raymond Hemmecke, Silvia Lindn...