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» Learning Probabilistic Models of Relational Structure
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COLING
2008
15 years 3 months ago
An Integrated Probabilistic and Logic Approach to Encyclopedia Relation Extraction with Multiple Features
We propose a new integrated approach based on Markov logic networks (MLNs), an effective combination of probabilistic graphical models and firstorder logic for statistical relatio...
Xiaofeng Yu, Wai Lam
CORR
2010
Springer
193views Education» more  CORR 2010»
15 years 16 days ago
A Probabilistic Approach for Learning Folksonomies from Structured Data
Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach t...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor
TCSV
2008
202views more  TCSV 2008»
15 years 1 months ago
Probabilistic Object Tracking With Dynamic Attributed Relational Feature Graph
Object tracking is one of the fundamental problems in computer vision and has received considerable attention in the past two decades. The success of a tracking algorithm relies on...
Feng Tang, Hai Tao
AAAI
2008
15 years 4 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
IJAR
2010
152views more  IJAR 2010»
15 years 13 days 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...