In most current approaches of speech processing, information is extracted from the magnitude spectrum. However recent perceptual studies have underlined the importance of the phas...
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
We empirically evaluate several state-of-theart methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to se...
We revisit the idea of history-based parsing, and present a history-based parsing framework that strives to be simple, general, and flexible. We also provide a decoder for this pr...
Abstract. In this paper, we compare merging operators in possibilistic logic. We first propose an approach to evaluating the discriminating power of a merging operator. After that...