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» Monotonicity in Bayesian Networks
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132
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ML
2010
ACM
151views Machine Learning» more  ML 2010»
15 years 1 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
131
Voted
UAI
1993
15 years 4 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
140
Voted
UAI
1996
15 years 4 months ago
Learning Bayesian Networks with Local Structure
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Nir Friedman, Moisés Goldszmidt
120
Voted
ICPR
2006
IEEE
16 years 4 months ago
Switching Auxiliary Chains for Speech Recognition based on Dynamic Bayesian Networks
This paper investigates the problem of incorporating auxiliary information (e.g. pitch) for speech recognition using dynamic Bayesian networks (DBNs). Previous works usually model...
Hui Lin 0001, Zhijian Ou
128
Voted
ADMA
2006
Springer
121views Data Mining» more  ADMA 2006»
15 years 9 months ago
A New Polynomial Time Algorithm for Bayesian Network Structure Learning
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
Sanghack Lee, Jihoon Yang, Sungyong Park