Managing uncertain data using probabilistic frameworks has attracted much interest lately in the database literature, and a central computational challenge is probabilistic infere...
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
A serious threat to user privacy in new mobile and web2.0 applications stems from ‘social inferences’. These unwanted inferences are related to the users’ identity, current ...
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...
With resemblance of finite-state machines to some biological mechanisms in cells and numerous applications of finite automata in different fields, this paper uses analogies an...