Abstract. The much-publicized Netflix competition has put the spotlight on the application domain of collaborative filtering and has sparked interest in machine learning algorithms...
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
We have recently presented CarpeDiem, an algorithm that can be used for speeding up the evaluation of Supervised Sequential Learning (SSL) classifiers. CarpeDiem provides impress...
Abstract. We propose a SAT-based algorithm for incremental diagnosis of discrete-event systems. The monotonicity is ensured by a prediction window that uses the future observations...
Abstract. Measuring relational similarity between words is important in numerous natural language processing tasks such as solving analogy questions and classifying noun-modifier r...