Abstract. In previous research, we presented a dynamicprogramming-based EM (expectation-maximization) algorithm for parameterized logic programs, which is based on the structure sh...
Bayesian approaches have been shown to reduce the amount of overfitting that occurs when running the EM algorithm, by placing prior probabilities on the model parameters. We appl...
A recent trend in motion-based segmentation has been to rely on statistical procedures derived from ExpectationMaximization (EM) principles. EM-based approaches have various attra...
This paper discusses the application of the Expectation-Maximization (EM) clustering algorithm to the task of Chinese verb sense discrimination. The model utilized rich linguistic...
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
David Maxwell Chickering, David Heckerman, Christo...