Data perturbation is a popular technique for privacypreserving data mining. The major challenge of data perturbation is balancing privacy protection and data quality, which are no...
Biomedical research has been revolutionized by high-throughput techniques and the enormous amount of biological data they are able to generate. The interest shown over network mode...
Cristina Rubio-Escudero, Oscar Harari, Oscar Cord&...
In many digital control applications, data acquisition and process control are time-critical actions, assumed to be instantaneous and strictly periodic. However, aspects related t...
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
In any real-life identification problem, only a finite number of data points is available. On the other hand, almost all results in stochastic identification pertain to asymptotic...