The paper presents a new sampling methodology for Bayesian networks that samples only a subset of variables and applies exact inference to the rest. Cutset sampling is a network s...
In Genetic algorithms it is not easy to evaluate the confidence level in whether a GA run may have missed a complete area of good points, and whether the global optimum was found....
We present a framework for an automated generation of exact search tree algorithms for NP-hard problems. The purpose of our approach is two-fold--rapid development and improved up...
The aim of this work is to present a method for rounding quadratically converging algorithms that improves their performance. This method is able to reduce significantly the numbe...
We consider finite horizon Markov decision processes under performance measures that involve both the mean and the variance of the cumulative reward. We show that either randomiz...