This paper presents a new approach to inference in Bayesian networks. The principal idea is to encode the network by logical sentences and to compile the resulting encoding into an...
There is a growing interest in building probabilistic models with high order potentials (HOPs), or interactions, among discrete variables. Message passing inference in such models...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Tractable subsets of first-order logic are a central topic in AI research. Several of these formalisms have been used as the basis for first-order probabilistic languages. Howev...
We give an algorithm to model any given multiple stuck-at fault as a single stuck-at fault. The procedure requires insertion of at most ? ? ? modeling gates, when the multiplicity...
Yong Chang Kim, Vishwani D. Agrawal, Kewal K. Salu...