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» Explaining inferences in Bayesian networks
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EXACT
2009
13 years 5 months ago
Some Properties of Most Relevant Explanation
This paper provides a study of the theoretical properties of Most Relevant Explanation (MRE) [12]. The study shows that MRE defines an implicit soft relevance measure that enables ...
Changhe Yuan
SIGMOD
2006
ACM
123views Database» more  SIGMOD 2006»
14 years 7 months ago
Proactive identification of performance problems
We propose to demonstrate Fa, an automated tool for timely and accurate prediction of Service-Level-Agreement (SLA) violations caused by performance problems in database systems. ...
Songyun Duan, Shivnath Babu
IJAR
2010
152views more  IJAR 2010»
13 years 6 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...
KI
2010
Springer
13 years 5 months ago
Situation-Specific Intention Recognition for Human-Robot Cooperation
Recognizing human intentions is part of the decision process in many technical devices. In order to achieve natural interaction, the required estimation quality and the used comput...
Peter Krauthausen, Uwe D. Hanebeck
NIPS
1996
13 years 9 months ago
Continuous Sigmoidal Belief Networks Trained using Slice Sampling
Real-valued random hidden variables can be useful for modelling latent structure that explains correlations among observed variables. I propose a simple unit that adds zero-mean G...
Brendan J. Frey