8 search results - page 1 / 2 » Causal discovery of linear acyclic models with arbitrary dis... |
UAI
2008
13 years 6 months ago
2008
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
JMLR
2006
13 years 4 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 ...
ICONIP
2007
13 years 6 months ago
2007
Abstract. An effective way to examine causality is to conduct an experiment with random assignment. However, in many cases it is impossible or too expensive to perform controlled ...
UAI
2008
13 years 6 months ago
2008
We generalize Shimizu et al's (2006) ICA-based approach for discovering linear non-Gaussian acyclic (LiNGAM) Structural Equation Models (SEMs) from causally sufficient, conti...
NIPS
2008
13 years 6 months ago
2008
The discovery of causal relationships between a set of observed variables is a fundamental problem in science. For continuous-valued data linear acyclic causal models with additiv...