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» Models for Incomplete and Probabilistic Information
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EWCBR
2008
Springer
13 years 9 months ago
Instance-Based Label Ranking using the Mallows Model
In this paper, we introduce a new instance-based approach to the label ranking problem. This approach is based on a probability model on rankings which is known as the Mallows mode...
Weiwei Cheng, Eyke Hüllermeier
IJCV
2000
164views more  IJCV 2000»
13 years 7 months ago
Probabilistic Modeling and Recognition of 3-D Objects
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
Joachim Hornegger, Heinrich Niemann
ICPR
2004
IEEE
14 years 8 months ago
Evaluation of Three Optical Flow-Based Observation Models for Tracking
In this paper, we study the use of optical flow as a characteristic for tracking. We analyze the behavior of three flowbased observation models for particle filter algorithms, and...
José M. Fuertes, Manuel J. Lucena, Nicolas ...
PODS
2007
ACM
131views Database» more  PODS 2007»
14 years 7 months ago
Provenance semirings
We show that relational algebra calculations for incomplete databases, probabilistic databases, bag semantics and whyprovenance are particular cases of the same general algorithms...
Todd J. Green, Gregory Karvounarakis, Val Tannen
IJAR
2010
152views more  IJAR 2010»
13 years 5 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...