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IJAR
2007
130views more  IJAR 2007»
15 years 3 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
ICS
2004
Tsinghua U.
15 years 9 months ago
Scaling the issue window with look-ahead latency prediction
In contemporary out-of-order superscalar design, high IPC is mainly achieved by exposing high instruction level parallelism (ILP). Scaling issue window size can certainly provide ...
Yongxiang Liu, Anahita Shayesteh, Gokhan Memik, Gl...
PAAPP
2007
109views more  PAAPP 2007»
15 years 3 months ago
Relation rule mining
\Web users are nowadays confronted with the huge variety of available information sources whose content is not targeted at any specific group or layer. Recommendation systems aim...
Mehdi Adda, Rokia Missaoui, Petko Valtchev
ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
15 years 2 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
ICML
2005
IEEE
16 years 4 months ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes