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» The Structure of First-Order Causality
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KDD
2007
ACM
209views Data Mining» more  KDD 2007»
14 years 8 months ago
Temporal causal modeling with graphical granger methods
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
Andrew Arnold, Yan Liu, Naoki Abe
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 6 days ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
BMCBI
2011
13 years 2 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
JMLR
2010
134views more  JMLR 2010»
13 years 2 months ago
Bayesian Algorithms for Causal Data Mining
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...
IRCDL
2008
13 years 9 months ago
Automatic Document Organization Exploiting FOL Similarity-based Techniques
The organization of a document collection into meaningful groups is a fundamental issue in document management systems. The grouping can be carried out by performing a comparison ...
Stefano Ferilli, Teresa Maria Altomare Basile, Mar...