CORR
2012
Springer
12 years 1 days 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
12 years 4 months 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
12 years 11 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
12 years 11 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 2 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
13 years 6 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
13 years 11 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...