The paper presents a method for generating solutions of a constraint satisfaction problem (CSP) uniformly at random. The main idea is to express the CSP as a factored probability d...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
We propose a multivariate decision tree inference scheme by using the minimum message length (MML) principle (Wallace and Boulton, 1968; Wallace and Dowe, 1999). The scheme uses MM...
This paper introduces an information theoretic approach to verification of modular causal probabilistic models. We assume systems which are gradually extended by adding new functi...
Static checking can verify the absence of errors in a program, but often requires written annotations or specifications. As a result, static checking can be difficult to use effec...