Superfluous variables are often produced as the byproducts of program transformations, compilation, and poorly written code. These variables are irrelevant to the computational o...
Abstract. Adaptive consistency is a solving algorithm for constraint networks. Its basic step is variable elimination: it takes a network as input, and producesan equivalent networ...
Abstract. Variable elimination is the basic step of Adaptive Consistency 4 . It transforms the problem into an equivalent one, having one less variable. Unfortunately, there are ma...
We compare two approaches to Bayesian network inference, called variable elimination (VE) and arc reversal (AR). It is established that VE never requires more space than AR, and n...
Cory J. Butz, Junying Chen, Ken Konkel, Pawan Ling...
In this article we present the general architecture of a hybrid neuro-symbolic system for the selection and stepwise elimination of predictor variables and non-relevant individuals...