Terascale simulations produce data that is vast in spatial, temporal, and variable domains, creating a formidable challenge for subsequent analysis. Feature extraction as a data r...
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
The essence of exploration is acting to try to decrease uncertainty. We propose a new methodology for representing uncertainty in continuous-state control problems. Our approach, ...
We present a data-driven, unsupervised method for unusual
scene detection from static webcams. Such time-lapse
data is usually captured with very low or varying framerate.
This ...
Michael D. Breitenstein, Helmut Grabner, Luc Van G...
The size and complexity of systems based on multiple processing units demand techniques for the automatic diagnosis of their state. System-level diagnosis consists in determining ...