Office Location: | 215 Physics |
Office Phone: | (919) 660-6970 |
Email Address: | |
Web Page: | http://www.math.duke.edu/~mhuber |
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
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.