This work advances the Support Vector Machine (SVM) based approach for predictive modelling of failure time data as proposed in [1]. The main results concern a drastic reduction in...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
In this work, we developed classifiers to distinguish between four ovarian tumor types using Bayesian least squares support vector machines (LS-SVMs) and kernel logistic regression...
Ben Van Calster, Dirk Timmerman, Antonia C. Testa,...
Adapting stimuli to stabilize neural responses is an important problem in the context of cortical prostheses. This paper describes two approaches for stimulus adaptation using supp...
Dominik Brugger, Sergejus Butovas, Martin Bogdan, ...
In classification problems, Support Vector Machines maximize the margin of separation between two classes. While the paradigm has been successful, the solution obtained by SVMs is...
There has been a recent swell of interest in the automatic identification and extraction of opinions and emotions in text. In this paper, we present the first experimental results...