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» Ontology-Based Generation of Bayesian Networks
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ISBRA
2009
Springer
15 years 4 months ago
Using Gene Expression Modeling to Determine Biological Relevance of Putative Regulatory Networks
Identifying gene regulatory networks from high-throughput gene expression data is one of the most important goals of bioinformatics, but it remains difficult to define what makes a...
Peter Larsen, Yang Dai
79
Voted
PRICAI
2004
Springer
15 years 2 months ago
An Anytime Algorithm for Interpreting Arguments
Abstract. The problem of interpreting Natural Language (NL) discourse is generally of exponential complexity. However, since interactions with users must be conducted in real time,...
Sarah George, Ingrid Zukerman, Michael Niemann
94
Voted
EXACT
2009
14 years 7 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
JMLR
2006
118views more  JMLR 2006»
14 years 9 months ago
Learning Factor Graphs in Polynomial Time and Sample Complexity
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
Pieter Abbeel, Daphne Koller, Andrew Y. Ng
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
15 years 10 months ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...