CORR
2012
Springer
12 years 8 months ago
2012
Springer
We present a novel approach to constraintbased causal discovery, that takes the form of straightforward logical inference, applied to a list of simple, logical statements about ca...
AAAI
2011
13 years 13 days ago
2011
Blocking is a technique commonly used in manual statistical analysis to account for confounding variables. However, blocking is not currently used in automated learning algorithms...
JMLR
2010
13 years 7 months ago
2010
Recent evaluations have indicated that in practice, general methods for prediction which do not account for changes in the conditional distribution of a target variable given feat...
JMLR
2010
13 years 7 months ago
2010
This paper presents a game theoretic approach to causal discovery. The problem of causal discovery is framed as a game of the Scientist against Nature, in which Nature attempts to...
ICDM
2010
IEEE
13 years 10 months ago
2010
IEEE
In this paper, we study a new research problem of causal discovery from streaming features. A unique characteristic of streaming features is that not all features can be available ...
AAAI
2008
14 years 2 months ago
2008
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
PKDD
2009
Springer
14 years 7 months ago
2009
Springer
We consider causally sufficient acyclic causal models in which the relationship among the variables is nonlinear while disturbances have linear effects, and show that three princi...