We present a novel method for state minimization of incompletely-specified finite state machines. Where classic methods simply minimize the number of states, ours directly addre...
Performance model building is essential to predict the ability of an application to satisfy given levels of performance or to support the search for viable alternatives. Using aut...
In recent years, several methods have been proposed for the discovery of causal structure from non-experimental data. Such methods make various assumptions on the data generating ...
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
For many years, statistical machine translation relied on generative models to provide bilingual word alignments. In 2005, several independent efforts showed that discriminative m...