Learning Classifier Systems differ from many other classification techniques, in that new rules are constantly discovered and evaluated. This feature of LCS gives rise to an im...
It was recently proposed the use of Bayesian networks for object tracking. Bayesian networks allow to model the interaction among detected trajectories, in order to obtain a relia...
Arnaldo J. Abrantes, Jorge S. Marques, Pedro Mende...
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...
— This paper introduces an expectation-maximization (EM) algorithm within a wavelet domain Bayesian framework for semi-blind channel estimation of multiband OFDM based UWB commun...
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...