A naive Bayesian classifier is a probabilistic classifier based on Bayesian decision theory with naive independence assumptions, which is often used for ranking or constructing a...
Abstract. Quantitative verification techniques are able to establish system properties such as "the probability of an airbag failing to deploy on demand" or "the exp...
Collapsed Gibbs sampling is a frequently applied method to approximate intractable integrals in probabilistic generative models such as latent Dirichlet allocation. This sampling ...
The scarcity of available multi-track recordings constitutes a severe constraint on the training of probabilistic models for voice extraction from polyphonic music. We propose a n...
We propose a probabilistic network model, called asynchronous bounded expected delay (ABE), which requires a known bound on the expected message delay. In ABE networks all asynchr...