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EACL
2006
ACL Anthology
15 years 2 months ago
Bayesian Network, a Model for NLP?
The NLP systems often have low performances because they rely on unreliable and heterogeneous knowledge. We show on the task of non-anaphoric it identification how to overcome the...
Davy Weissenbacher
AI
2010
Springer
15 years 24 days ago
Understanding the scalability of Bayesian network inference using clique tree growth curves
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Ole J. Mengshoel
93
Voted
CORR
2000
Springer
85views Education» more  CORR 2000»
15 years 14 days ago
Conditional Plausibility Measures and Bayesian Networks
A general notion of algebraic conditional plausibility measures is de ned. Probability measures, ranking functions, possibility measures, and under the appropriate de nitions sets...
Joseph Y. Halpern
107
Voted
ML
2010
ACM
151views Machine Learning» more  ML 2010»
14 years 11 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
UAI
1993
15 years 2 months ago
Using Causal Information and Local Measures to Learn Bayesian Networks
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
Wai Lam, Fahiem Bacchus