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» Introduction to Causal Inference
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CORR
2010
Springer
154views Education» more  CORR 2010»
13 years 10 months ago
Causal Markov condition for submodular information measures
The causal Markov condition (CMC) is a postulate that links observations to causality. It describes the conditional independences among the observations that are entailed by a cau...
Bastian Steudel, Dominik Janzing, Bernhard Sch&oum...
CVPR
2012
IEEE
12 years 6 days ago
Bridging the past, present and future: Modeling scene activities from event relationships and global rules
This paper addresses the discovery of activities and learns the underlying processes that govern their occurrences over time in complex surveillance scenes. To this end, we propos...
Jagannadan Varadarajan, Rémi Emonet, Jean-M...
JMLR
2010
194views more  JMLR 2010»
13 years 4 months ago
Graphical Gaussian modelling of multivariate time series with latent variables
In time series analysis, inference about causeeffect relationships among multiple times series is commonly based on the concept of Granger causality, which exploits temporal struc...
Michael Eichler
IRAL
2003
ACM
14 years 3 months ago
Question-Answering based on virtually integrated lexical knowledge base
This paper proposes an algorithm for causality inference based on a set of lexical knowledge bases that contain information about such items as event role, is-a hierarchy, relevan...
Key-Sun Choi, Jae-Ho Kim, Masaru Miyazaki, Jun Got...