This paper considers online stochastic optimization problems where uncertainties are characterized by a distribution that can be sampled and where time constraints severely limit t...
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
In this paper, a multiobjective (MO) learning approach to image feature extraction is described, where Pareto-optimal interest point (IP) detectors are synthesized using genetic p...
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...