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» A Combination Method for Generating Interpolants
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UAI
2003
15 years 7 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
ML
2008
ACM
222views Machine Learning» more  ML 2008»
15 years 6 months ago
Boosted Bayesian network classifiers
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
JAIR
1998
97views more  JAIR 1998»
15 years 6 months ago
The Divide-and-Conquer Subgoal-Ordering Algorithm for Speeding up Logic Inference
It is common to view programs as a combination of logic and control: the logic part de nes what the program must do, the control part how to do it. The Logic Programming paradigm ...
Oleg Ledeniov, Shaul Markovitch
WIOPT
2010
IEEE
15 years 4 months ago
Enhancing RRM optimization using a priori knowledge for automated troubleshooting
—The paper presents a methodology that combines statistical learning with constraint optimization by locally optimizing Radio Resource Management (RRM) or system parameters of po...
Moazzam Islam Tiwana, Zwi Altman, Berna Sayra&cced...
ICST
2011
IEEE
14 years 10 months ago
It is Not the Length That Matters, It is How You Control It
—The length of test cases is a little investigated topic in search-based test generation for object oriented software, where test cases are sequences of method calls. While intui...
Gordon Fraser, Andrea Arcuri