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FSS
2008
87views more  FSS 2008»
15 years 7 months ago
Representing parametric probabilistic models tainted with imprecision
Numerical possibility theory, belief function have been suggested as useful tools to represent imprecise, vague or incomplete information. They are particularly appropriate in unc...
Cédric Baudrit, Didier Dubois, Nathalie Per...
BMVC
2010
15 years 5 months ago
Back to the Future: Learning Shape Models from 3D CAD Data
Recognizing 3D objects from arbitrary view points is one of the most fundamental problems in computer vision. A major challenge lies in the transition between the 3D geometry of o...
Michael Stark, Michael Goesele, Bernt Schiele
CORR
2007
Springer
130views Education» more  CORR 2007»
15 years 7 months ago
Lagrangian Relaxation for MAP Estimation in Graphical Models
Abstract— We develop a general framework for MAP estimation in discrete and Gaussian graphical models using Lagrangian relaxation techniques. The key idea is to reformulate an in...
Jason K. Johnson, Dmitry M. Malioutov, Alan S. Wil...
169
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SOFTVIS
2005
ACM
16 years 1 months ago
Exploiting UML dynamic object modeling for the visualization of C++ programs
In this paper we present an approach to modeling and visualizing the dynamic interactions among objects in a C++ application. We exploit UML diagrams to expressively visualize bot...
Brian A. Malloy, James F. Power
ATVA
2007
Springer
90views Hardware» more  ATVA 2007»
15 years 11 months ago
Efficient Approximate Verification of Promela Models Via Symmetry Markers
We present a new verification technique for Promela which exploits state-space symmetries induced by scalarset values used in a model. The technique involves efficiently computing ...
Dragan Bosnacki, Alastair F. Donaldson, Michael Le...