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» Learning locally minimax optimal Bayesian networks
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FLAIRS
2006
13 years 8 months ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
ICML
2004
IEEE
14 years 7 months ago
Learning large margin classifiers locally and globally
A new large margin classifier, named MaxiMin Margin Machine (M4 ) is proposed in this paper. This new classifier is constructed based on both a "local" and a "globa...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
UAI
1998
13 years 8 months ago
The Bayesian Structural EM Algorithm
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
Nir Friedman
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
13 years 8 months ago
iBOA: the incremental bayesian optimization algorithm
This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of t...
Martin Pelikan, Kumara Sastry, David E. Goldberg
NIPS
1990
13 years 8 months ago
Convergence of a Neural Network Classifier
In this paper, we show that the LVQ learning algorithm converges to locally asymptotic stable equilibria of an ordinary differential equation. We show that the learning algorithm ...
John S. Baras, Anthony LaVigna