When large amount of statistical information about power system component failure rate is available, statistical parametric models can be developed for predictive maintenance. Oft...
Miroslav Begovic, Petar M. Djuric, Joshua Perkel, ...
Morfette is a modular, data-driven, probabilistic system which learns to perform joint morphological tagging and lemmatization from morphologically annotated corpora. The system i...
Grzegorz Chrupala, Georgiana Dinu, Josef van Genab...
Many existing approaches to collaborative filtering can neither handle very large datasets nor easily deal with users who have very few ratings. In this paper we present the Prob...
Large systems of agents deployed in a real-world environment face threats to their problem solving performance that are independent of the complexity of the problem or the charact...
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...