Production grids are complex and highly variable systems whose behavior is not well understood and difficult to anticipate. The goal of this study is to estimate the impact of the ...
Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
We develop a decision-theoretic method that yields approximate, low cost troubleshooting plans by making more relevant observations and devoting more time to generate a plan. The ...
This paper studies types and probabilistic bisimulations for a timed -calculus as an effective tool for a compositional analysis of probabilistic distributed behaviour. The types c...
Probabilistic processes appear naturally in various contexts, with applications to Business Processes, XML data management and more. Many models for specifying and querying such p...