Research Interests for Mark Huber

For high dimensional problems, Monte Carlo samples are a fast way to estimate integrals without the need to construct grids with exponentially many points. Within Monte Carlo simulation, my primary area of expertise is perfect sampling, algorithms that generate random variates from a variety of distributions that are interesting from either a theoretical or pratical point of view.

Keywords:

perfect simulation, Monte Carlo algorithms, mixing times

Current projects:

approximating the permanent

studying speed of covergence for parallel tempering

Markov chains for generating regular graphs

restoration of grayscale images

applications of the Randomness Recycler

Recent Publications

1. M. L. Huber and R. L. Wolpert, Perfect Simulation of Matern Type III Repulsive Point Processes (Submitted, September, 2008) [abs]
2. M. Huber, Perfect simulation with exponential tails, Random Structures and Algorithms, vol. 33 no. 1 (August, 2008), pp. 29--43, Wiley InterScience [abs]
3. M. Huber, Spatial Birth-Death-Swap Chains, Bernoulli (Submitted, May, 2008) [abs]
4. M. Huber, Spatial point processes, in Handbook of MCMC, edited by Brooks, Gelman, Jones, Meng (Accepted, April, 2008)
5. James A. Fill, Mark L. Huber, Linear expected time perfect generation of proper colorings of low degree graphs (Preprint, 2008) [abs]