SuperParent-One-Dependence Estimators (SPODEs) loosen Naive-Bayes’ attribute independence assumption by allowing each attribute to depend on a common single attribute (superpare...
Ying Yang, Kevin B. Korb, Kai Ming Ting, Geoffrey ...
This paper discusses the performance of a hybrid system which consists of EDP and GP. EDP, Estimation of Distribution Programming, is the program evolution method based on the prob...
We address the question of how to choose between different likelihood functions for motion estimation. To this end, we formulate motion estimation as a problem of Bayesian inferen...
In this paper, we solve the problem of detecting the entries of a sparse finite-alphabet signal from a limited amount of data, for instance obtained by compressive sampling. While...
Abstract. Causal modeling, such as noisy-OR, reduces probability parameters to be acquired in constructing a Bayesian network. Multiple causes can reinforce each other in producing...