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...
We propose an approach to lossy source coding, utilizing ideas from Gibbs sampling, simulated annealing, and Markov Chain Monte Carlo (MCMC). The idea is to sample a reconstructio...
— In this paper, we propose a novel low complexity soft-in soft-out (SISO) equalizer using the Markov chain Monte Carlo (MCMC) technique. Direct application of MCMC to SISO equal...
Recently developed adaptive Markov chain Monte Carlo (MCMC) methods have been applied successfully to many problems in Bayesian statistics. Grapham is a new open source implementat...
This paper studies a framework for matching an unknown
number of corresponding structures in two images
(shapes), motivated by detecting objects in cluttered background
and lear...