A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
: This article presents a rule–based agent mechanism as the kernel of a ubiquitous end–user, UI–independent programming system. The underlying goal of our work is to allow en...
We propose an approach to adjective-noun composition (AN) for corpus-based distributional semantics that, building on insights from theoretical linguistics, represents nouns as ve...
We propose a region-based method to extract semantic foreground regions from color video sequences with static backgrounds. First, we introduce a new distance measure for backgrou...
This work presents a new approach to discriminative speaker verification. Rather than estimating speaker models, or a model that discriminates between a speaker class and the cla...