Duke Probability Theory and Applications
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Mark Huber, Assistant Professor of Mathematics

Mark Huber
Contact Info:
Office Location:  215 Physics Bldg
Office Phone:  (919) 660-6970
Email Address: send me a message
Web Page:  http://www.math.duke.edu/~mhuber

Teaching (Fall 2008):

Education:

Doctorate of Philosophy Cornell University 1999
BS Harvey Mudd College 1994
B.S. in Mathematics at Harvey Mudd College, 1994
Masters in Operations Research at Cornell University, 1997
Ph.D. in Operations Research at Cornell University, 1999
Specialties:

Probability
Applied Math
Research Interests: Monte Carlo simulation and stochastic computation

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.

Keywords:

perfect simulation • Monte Carlo algorithms • mixing times

Curriculum Vitae
Current Ph.D. Students  

  • Wai (Jenny) J. Law  
Postdocs Mentored

  • Ruriko Yoshida (August 26, 2004 - May 31, 2006)  
Recent Publications   (More Publications)

  1. M. Huber, Perfect simulation with exponential tails, Random Structures and Algorithms, vol. 33 no. 1 (August, 2008), pp. 29--43, Wiley InterScience  [abs]
  2. M. Huber, Spatial Birth-Death-Swap Chains, Bernoulli (Submitted, May, 2008)  [abs]
  3. M. Huber, Spatial point processes, in Handbook of MCMC, edited by Brooks, Gelman, Jones, Meng (Accepted, April, 2008)
  4. M. Huber, Multiratio Metropolis-Hastings for distributions with several unknown normalizing constants, Annals of Applied Probability (Submitted, 2008)  [abs]
  5. James A. Fill, Mark L. Huber, Linear expected time perfect generation of proper colorings of low degree graphs (Preprint, 2008)  [abs]
Recent Grant Support

  • Perfect sampling for high dimensional integration, NSF, CAREER: DMS-05-48153, 2006/01-2007/12.