Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...
Of all of the challenges which face the selection of relevant features for predictive data mining or pattern recognition modeling, the adaptation of computational intelligence tec...
Collapsed Gibbs sampling is a frequently applied method to approximate intractable integrals in probabilistic generative models such as latent Dirichlet allocation. This sampling ...
We show a method for parallelizing top down dynamic programs in a straightforward way by a careful choice of a lock-free shared hash table implementation and randomization of the ...
Alex Stivala, Peter J. Stuckey, Maria Garcia de la...
We say a countable model A has a 0-basis if the types realized in A are uniformly computable. We say A has a (d-)decidable copy if there exists a model B = A such that the element...