Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
The success of schema integration in multidatabase systems relies heavily on the determination of complete and refined correspondence relationships between them. So, the candidate...
In this paper the classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then the whole model is placed into the framework of...
according to this definition2. Each elementary tree is constrained to have at least one terminal at its frontier which serves as 'head' (or 'anchor'). Sentence...
We reinvestigate the oblivious RAM concept introduced by Goldreich and Ostrovsky, which enables a client, that can store locally only a constant amount of data, to store remotely ...