With the growing scale of current computing systems, traditional configuration tuning methods become less effective because they usually assume a small number of parameters in the...
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 ...
This research introduces a general class of functions serving as generalized neuron models to be used in artificial neural networks. They are cast in the common framework of comp...
We combine techniques originally developed for refutational first-order theorem proving within the clause tree framework with techniques for minimal model computation developed wi...
Peter Baumgartner, Joseph Douglas Horton, Bruce Sp...
This paper presents a unified probabilistic framework for denoising and dereverberation of speech signals. The framework transforms the denoising and dereverberation problems into...