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» Learning Bayesian Networks from Incomplete Databases
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MLDM
2009
Springer
15 years 4 months ago
An Evidence-Driven Probabilistic Inference Framework for Semantic Image Understanding
This work presents an image analysis framework driven by emerging evidence and constrained by the semantics expressed in an ontology. Human perception, apart from visual stimulus a...
Spiros Nikolopoulos, Georgios Th. Papadopoulos, Io...
ISWC
2003
IEEE
15 years 3 months ago
Sensing and Modeling Human Networks using the Sociometer
Knowledge of how people interact is important in many disciplines, e.g. organizational behavior, social network analysis, information diffusion and knowledge management applicatio...
Tanzeem Choudhury, Alex Pentland
ICML
2009
IEEE
15 years 10 months ago
Learning Markov logic network structure via hypergraph lifting
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
Stanley Kok, Pedro Domingos
AIED
2009
Springer
15 years 4 months ago
Detecting the Learning Value of Items In a Randomized Problem Set
Researchers that make tutoring systems would like to know which pieces of educational content are most effective at promoting learning among their students. Randomized controlled e...
Zachary A. Pardos, Neil T. Heffernan
BMCBI
2010
153views more  BMCBI 2010»
14 years 10 months ago
MimoSA: a system for minimotif annotation
Background: Minimotifs are short peptide sequences within one protein, which are recognized by other proteins or molecules. While there are now several minimotif databases, they a...
Jay Vyas, Ronald J. Nowling, Thomas Meusburger, Da...