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» Selectivity Estimation using Probabilistic Models
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ICPR
2004
IEEE
15 years 10 months ago
A Fast Discriminant Approach to Active Object Recognition and Pose Estimation
This paper presents a new criterion for viewpoint selection in the context of active Bayesian object recognition and pose estimation. Recognition is performed by probabilistically...
Catherine Laporte, Rupert Brooks, Tal Arbel
SIGIR
2010
ACM
14 years 9 months ago
A joint probabilistic classification model for resource selection
Resource selection is an important task in Federated Search to select a small number of most relevant information sources. Current resource selection algorithms such as GlOSS, COR...
Dzung Hong, Luo Si, Paul Bracke, Michael Witt, Tim...
GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
15 years 1 months ago
Probabilistic modeling for continuous EDA with Boltzmann selection and Kullback-Leibeler divergence
This paper extends the Boltzmann Selection, a method in EDA with theoretical importance, from discrete domain to the continuous one. The difficulty of estimating the exact Boltzma...
Yunpeng Cai, Xiaomin Sun, Peifa Jia
ACCV
2010
Springer
14 years 4 months ago
Estimating Meteorological Visibility Using Cameras: A Probabilistic Model-Driven Approach
Estimating the atmospheric or meteorological visibility distance is very important for air and ground transport safety, as well as for air quality. However, there is no holistic ap...
Nicolas Hautière, Raouf Babari, Eric Dumont...
SMA
1993
ACM
107views Solid Modeling» more  SMA 1993»
15 years 1 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