We consider analysis of complex stochastic models based upon partial information. MCMC and reversible jump MCMC are often the methods of choice for such problems, but in some situ...
Abstract. We introduce a new mixed method for linear elasticity. The novelty is a simplicial element for the approximate stress. For every positive integer k, the row-wise divergen...
We present a new approach for the discriminative training
of continuous-valued Markov Random Field (MRF)
model parameters. In our approach we train the MRF
model by optimizing t...
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 ...
— We propose a new one-shot collaborative filtering method. In contrast to the conventional methods, which predict unobserved ratings individually and independently, our method ...