In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
We present a sequential Monte Carlo method applied to additive noise compensation for robust speech recognition in time-varying noise. The method generates a set of samples accord...
The purpose of this paper is to describe (a) why simulation is necessary to evaluate check-in, (b) a simulation toolbox for check-in counters and (c) Two case studies for Amsterda...
— In this paper, we propose a new supervised learning method whereby information is controlled by the associated cost in an intermediate layer, and in an output layer, errors bet...
We propose a method for constructing Dempster-Shafer belief functions modeling the trust of a given agent (the evaluator) in another (the target) by combining statistical informat...