166 search results - page 4 / 34 » Identifying Linear Causal Effects |
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
The importance of bringing causality into play when designing feature selection methods is more and more acknowledged in the machine learning community. This paper proposes a filt...
JMLR
2006
13 years 7 months ago
2006
In recent years, several methods have been proposed for the discovery of causal structure from non-experimental data. Such methods make various assumptions on the data generating ...
UAI
2001
13 years 8 months ago
2001
An instrument is a random variable that is uncorrelated with certain (unobserved) error terms and, thus, allows the identification of structural parameters in linear models. In no...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Nonlinear ICA may not result in nonlinear blind source separation, since solutions to nonlinear ICA are highly non-unique. In practice, the nonlinearity in the data generation pro...
JMLR
2011
13 years 2 months ago
2011
This paper reviews a class of methods to perform causal inference in the framework of a structural vector autoregressive model. We consider three different settings. In the first ...