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» Learning Bayesian Networks from Incomplete Databases
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ICPR
2008
IEEE
15 years 11 months ago
Visual features with semantic combination using Bayesian network for a more effective image retrieval
In many vision problems, instead of having fully annotated training data, it is easier to obtain just a subset of data with annotations, because it is less restrictive for the use...
Sabine Barrat, Salvatore Tabbone
ICML
2003
IEEE
15 years 10 months ago
Learning with Knowledge from Multiple Experts
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers...
Matthew Richardson, Pedro Domingos
TROB
2008
207views more  TROB 2008»
14 years 9 months ago
Learning Object Affordances: From Sensory-Motor Coordination to Imitation
Affordances encode relationships between actions, objects and effects. They play an important role on basic cognitive capabilities such as prediction and planning. We address the p...
Luis Montesano, Manuel Lopes, Alexandre Bernardino...
CORR
2010
Springer
193views Education» more  CORR 2010»
14 years 8 months 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
ICDAR
2003
IEEE
15 years 3 months ago
Learning the lexicon from raw texts for open-vocabulary Korean word recognition
In this paper, we propose a novel method of building a language model for open-vocabulary Korean word recognition. Due to the complex morphology of Korean, it is inappropriate to ...
Sungho Ryu, Jin Hyung Kim