15 search results - page 1 / 3 » Causal learning without DAGs |
JMLR
2010
13 years 14 days ago
2010
Causal learning methods are often evaluated in terms of their ability to discover a true underlying directed acyclic graph (DAG) structure. However, in general the true structure ...
JMLR
2010
13 years 14 days ago
2010
Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a ...
JMLR
2010
13 years 14 days ago
2010
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
NIPS
2008
13 years 7 months ago
2008
In many domains, data are distributed among datasets that share only some variables; other recorded variables may occur in only one dataset. While there are asymptotically correct...
UAI
2001
13 years 7 months ago
2001
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Baye...