The manipulation of large-scale document data sets often involves the processing of a wealth of features that correspond with the available terms in the document space. The employm...
A “graphics for vision” approach is proposed to address the problem of reconstruction from a large and imperfect data set: reconstruction on demand by tensor voting, or ROD-TV...
We present an improvement of the SAT-based Unbounded Model Checking (UMC) algorithm. UMC, a symbolic approach introduced in [7], uses propositional formulas in conjunctive normal ...
In statistics, mixture models consisting of several component subpopulations are used widely to model data drawn from heterogeneous sources. In this paper, we consider maximum lik...
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...