In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
In this paper we propose a uniform approach to deal with incremental problems on digraphs and with decremental problems on dags generalizing a technique used by La Poutr´e and va...
A range query applies an aggregation operation over all selected cells of an OLAP data cube where the selection is speci ed by providing ranges of values for numeric dimensions. W...
The large number of spectral variables in most data sets encountered in spectral chemometrics often renders the prediction of a dependent variable uneasy. The number of variables ...
Abstract. We extend the setting of Satisfiability Modulo Theories (SMT) by introducing a theory of costs C, where it is possible to model and reason about resource consumption and ...