In high-dimensional classification problems it is infeasible to include enough training samples to cover the class regions densely. Irregularities in the resulting sparse sample d...
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
The evaluation of successor or predecessor state spaces through time progress is a central component in the model-checking algorithm of dense-time automata. The definition of the t...
— In this paper we use partially ordered sets (posets) to study decentralized control problems arising in different settings. We show that time delayed systems with certain dela...
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...