A linear mixture of experts is used to combine three standard IR systems. The parameters for the mixture are determined automatically through training on document relevance assessments via optimization of a rank-order statistic which is empirically correlated with average precision. The mixture improves performance in some cases and degrades it in others, with the degradations possibly due to t...

In this paper we investigate mixture of experts problems in the context of Local-Global Neural Networks. This type of architecture was originaly conceived for functional approximation and interpolation problems. Numerical experiments are presented, showing quite nice solutions. Because of its local characteristics, this type of approach brings the advantage of improving interpretability.

A new approach for the automatic detection of drug-induced organ toxicities based on Nuclear Magnetic Resonance Spectroscopy data from biofluids is presented in this paper. Spectral data from biofluids contain information on the concentration of various substances, but the combination of only a small subset of these cues is putatively useful for classification of new samples. We propose to divi...

Th is paper addresses the role of experts in decision-making in local government. Departing from theories about professionals and technocrats in decision-making processes, the question arises as to how much infl uence these experts have in policymaking processes. Th e paper addresses this question and discusses the role of western experts in adapting the social security system to EU requirement...