A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a pos...
We present a model of recursive and impredicatively quantified types with mutable references. We interpret in this model all of the type constructors needed for typed intermediate...
Andrew W. Appel, Christopher D. Richards, Jé...
Background: The Generalized Hidden Markov Model (GHMM) has proven a useful framework for the task of computational gene prediction in eukaryotic genomes, due to its flexibility an...
William H. Majoros, Mihaela Pertea, Arthur L. Delc...
Building a model using machine learning that can classify the sentiment of natural language text often requires an extensive set of labeled training data from the same domain as t...
Abstract. We present a trust model extension that attempts to relax the assumptions that are currently taken by the majority of existing trust models: (i) proven identity of agents...