We describe a novel max-margin parameter learning approach for structured prediction problems under certain non-decomposable performance measures. Structured prediction is a commo...
In this paper we present analysis and calibration techniques that exploit knowledge about a multi agent society in order to calibrate the system parameters of a corresponding socie...
Background: Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of f...
This paper examines the identification of multi-input systems. Motivated by an experiment design problem (should one excite the various inputs simultaneously or separately), we ex...
Michel Gevers, Ljubisa Miskovic, Dominique Bonvin,...
Background: Computational gene prediction continues to be an important problem, especially for genomes with little experimental data. Results: I introduce the SNAP gene finder whi...