Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of ...
We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
There are many academic and commercial stream processing engines (SPEs) today, each of them with its own execution semantics. This variation may lead to seemingly inexplicable diď...
BORM Object Behavior Analysis (BOBA) is a first stage in a process of object modeling which has proved successful in a wide number of applications. This paper discusses this metho...
—One of main issues in point matching is the choice of the mapping function and the computation of its optimal hyperparameters. In this paper, we propose an attractive approach t...