In our previous work, we have developed sparse least squares support vector regressors (sparse LS SVRs) trained in the primal form in the reduced empirical feature space. In this p...
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 ...
The paper presents two experiments of unsupervised classification of Italian noun phrases. The goal of the experiments is to identify the most prominent contextual properties that...
How does one extract unknown but stereotypical events that are linearly superimposed within a signal with variable latencies and variable amplitudes? One could think of using temp...
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...