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...
The efficient mapping of program parallelism to multi-core processors is highly dependent on the underlying architecture. This paper proposes a portable and automatic compiler-bas...
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
We introduce three ensemble machine learning methods for analysis of biological DNA binding by transcription factors (TFs). The goal is to identify both TF target genes and their ...