Sciweavers

8970 search results - page 7 / 1794
» Learning to Learn Causal Models
Sort
View
ICML
2010
IEEE
15 years 21 days ago
Modeling Interaction via the Principle of Maximum Causal Entropy
The principle of maximum entropy provides a powerful framework for statistical models of joint, conditional, and marginal distributions. However, there are many important distribu...
Brian Ziebart, J. Andrew Bagnell, Anind K. Dey
FUIN
2008
108views more  FUIN 2008»
14 years 10 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel
IROS
2006
IEEE
146views Robotics» more  IROS 2006»
15 years 5 months ago
Adaptive Causal Models for Fault Diagnosis and Recovery in Multi-Robot Teams
— This paper presents an adaptive causal model method (adaptive CMM) for fault diagnosis and recovery in complex multi-robot teams. We claim that a causal model approach is effec...
Lynne E. Parker, Balajee Kannan
BMCBI
2011
14 years 6 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
ACL
2008
15 years 1 months ago
Learning Semantic Links from a Corpus of Parallel Temporal and Causal Relations
Finding temporal and causal relations is crucial to understanding the semantic structure of a text. Since existing corpora provide no parallel temporal and causal annotations, we ...
Steven Bethard, James H. Martin