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CORR
2011
Springer
174views Education» more  CORR 2011»
14 years 9 months ago
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
Yoshitaka Kameya, Taisuke Sato
ECSQARU
2001
Springer
15 years 10 months ago
An Empirical Investigation of the K2 Metric
Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
Christian Borgelt, Rudolf Kruse
ICML
2003
IEEE
15 years 10 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens
NN
2000
Springer
165views Neural Networks» more  NN 2000»
15 years 5 months ago
Learning non-stationary conditional probability distributions
While sophisticated neural networks and graphical models have been developed for predicting conditional probabilities in a non-stationary environment, major improvements in the tr...
Dirk Husmeier
NN
2007
Springer
173views Neural Networks» more  NN 2007»
15 years 5 months ago
An enhanced self-organizing incremental neural network for online unsupervised learning
An enhanced self-organizing incremental neural network (ESOINN) is proposed to accomplish online unsupervised learning tasks. It improves the self-organizing incremental neural ne...
Shen Furao, Tomotaka Ogura, Osamu Hasegawa