Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
Wonsik Kim (Seoul National University), Kyoung Mu ...
Monte Carlo methods and their subsequent simulated annealing are able to minimize general energy functions. However, the slow convergence of simulated annealing compared with more ...
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...