This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to nondifferentiable objective functions and trades off explor...
Abstract. Many statistical signal processing problems found in wireless communications involves making inference about the transmitted information data based on the received signal...
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Markov chain Monte Carlo has been the standard technique for inferring the posterior distribution of genome rearrangement scenarios under a Bayesian approach. We present here a neg...
: Kernel density estimation for multivariate data is an important technique that has a wide range of applications. However, it has received significantly less attention than its un...