In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Background: Many protein sequences are still poorly annotated. Functional characterization of a protein is often improved by the identification of its interaction partners. Here, ...
Andreas Henschel, Christof Winter, Wan Kyu Kim, Mi...
In this paper, we describe new methodologies for reinforcing the social consensus building of the multicultural coexistence assistance using participatory simulation in civil soci...
This work studies the impact of using dynamic information as features in a machine learning algorithm for the prediction task of classifying critically ill patients in two classes ...