Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
While decision trees have been used primarily for classification, they can also model regression or function approximation. Like classification trees, regression trees often yield...
Afiniteelement simulationframeworkforcuttingand fracturing model without remeshing is presented. The main idea of proposed method is adding a discontinuous function for the standa...
Determining similarities among data objects is a core task of content-based multimedia retrieval systems. Approximating data object contents via flexible feature representations, ...
This paper formalizes Feature Selection as a Reinforcement Learning problem, leading to a provably optimal though intractable selection policy. As a second contribution, this pape...