Abstract. We introduce a nonmonotonic framework for belief revision in which reasoning about the reliability of different pieces of information based on meta-knowledge about the in...
This paper introduces a Bayesian method for clustering dynamic processes. The method models dynamics as Markov chains and then applies an agglomerative clustering procedure to disc...
We discuss the almost-sure convergence of a broad class of sampling algorithms for multi-stage stochastic linear programs. We provide a convergence proof based on the finiteness o...
This paper describes a supervised, knowledge-intensive approach to the automatic identification of semantic relations between nominals in English sentences. The system employs di...
Roxana Girju, Brandon Beamer, Alla Rozovskaya, A. ...
We present a Gaussian Mixture model for detecting different types of figurative language in context. We show that this model performs well when the parameters are estimated in an ...