Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
Background: Growing interest on biological pathways has called for new statistical methods for modeling and testing a genetic pathway effect on a health outcome. The fact that gen...
Background: Coalescent simulations have proven very useful in many population genetics studies. In order to arrive to meaningful conclusions, it is important that these simulation...
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Relevance feedback has been demonstrated to be an effective strategy for improving retrieval accuracy. The existing relevance feedback algorithms based on language models and vect...