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FSS
2008
87views more  FSS 2008»
13 years 5 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...
ICLP
2004
Springer
13 years 10 months ago
Possible Worlds Semantics for Probabilistic Logic Programs
Abstract. In this paper we consider a logic programming framework for reasoning about imprecise probabilities. In particular, we propose a new semantics, for the Probabilistic Logi...
Alex Dekhtyar, Michael I. Dekhtyar
SMA
1993
ACM
107views Solid Modeling» more  SMA 1993»
13 years 9 months ago
Relaxed parametric design with probabilistic constraints
: Parametric design is an important modeling paradigm in computer aided design. Relationships (constraints) between the degrees of freedom (DOFs) of the model, instead of the DOFs ...
Yacov Hel-Or, Ari Rappoport, Michael Werman
ECCV
2004
Springer
14 years 6 months ago
A Robust Probabilistic Estimation Framework for Parametric Image Models
Models of spatial variation in images are central to a large number of low-level computer vision problems including segmentation, registration, and 3D structure detection. Often, i...
Maneesh Kumar Singh, Himanshu Arora, Narendra Ahuj...
FLAIRS
2006
13 years 6 months ago
Some Second Order Effects on Interval Based Probabilities
In real-life decision analysis, the probabilities and values of consequences are in general vague and imprecise. One way to model imprecise probabilities is to represent a probabi...
David Sundgren, Mats Danielson, Love Ekenberg