99 search results - page 2 / 20 » Learning Causal Structure from Overlapping Variable Sets |
JMLR
2006
13 years 7 months ago
2006
We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause...
NIPS
2000
13 years 9 months ago
2000
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
KDD
2003
ACM
14 years 8 months ago
2003
ACM
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
JMLR
2010
13 years 2 months ago
2010
Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...
AAAI
2006
13 years 9 months ago
2006
We offer a complete characterization of the set of distributions that could be induced by local interventions on variables governed by a causal Bayesian network of unknown structu...