Giving Statistics Seminar at The Ohio State statistics department next week
Posted by markhuber in Uncategorized on May 16, 2012
I am speaking in the statistics seminar at The Ohio State University next week. The title of my talk is “Fast approximation algorithms for partition functions of Gibbs distributions”. It will be held in the Eighteenth Avenue Building, Room 170 on Thursday, May 24th from 3:30 to 4:30 pm. More details can be found here.
Abstract: Finding the partition function of Gibbs distributions has applications in model selection and building estimators for parameters of spatial models. This talk will present a new algorithm for estimating these partition functions. The method combines a well balanced cooling schedule created through a technique called TPA and a product importance sampler. One advantage of the algorithm over existing methods is the standard deviation of the estimate can be bounded theoretically. That is to say, unlike most algorithms where the standard deviation must itself be estimated, the standard deviation of this algorithm is fixed ahead of time by the use. The number of samples necessary to build a close estimate grows almost linearly in the logarithm of the partition function, making the approach suitable for high dimensional problems. The samples needed for the estimate can be generated rapidly by methods such as parallel tempering.
Giving an Algebra/Number Theory/Combinatorics Seminar this Tuesday
Posted by markhuber in Uncategorized on January 22, 2012
This Tuesday I’m starting off the talks for the Spring in the Algebra/Number Theory/Combinatorics Seminar here in Claremont. It will be at 12:15 on 24 Jan 2012 in Millikan 134. Complete details can be found here. The title is “A gadget for reducing the Ising model to matchings”, and it is joint work that I did with my first graduate student, Jenny Law.
Abstract: In my talk last semester in the seminar, I presented a classic result: the problem of counting the number of solutions to a logic formula can be turned into a problem of summing weighted perfect matchings in a graph. The key idea was the use of a combinatorial “gadget”. In this talk I’ll present a gadget developed with my first graduate student, Jenny Law, that allows for what is called a simulation reduction. The reduction works as follows: if you are able to sample randomly from a weighted distribution on perfect matchings in a graph, then you can also simulate from the Ising model, a classical model from statistical physics that has been heavily studied since its inception in the 1920′s. (http://arxiv.org/abs/0907.0477)
Posted UCLA talk on website
Posted by markhuber in Uncategorized on December 8, 2011
My talk at UCLA is now available on my website at http://www.cmc.edu/pages/faculty/MHuber/Research/talks/huber_talk_2011h.pdf. They have an interesting system there. The grad students go out for lunch with the speaker and can ask questions or just shoot the breeze. Then after the talk the students have a half an hour to just ask whatever questions come to mind about the talk and the contents. It is much more relaxed than the usual “five minutes to answer all you questions” at the end of the talk, and allows for a lot more depth.
Added talk at University of Missouri at St. Louis to website
Posted by markhuber in Invited Talks on November 11, 2011
The talk that I gave at UMSL can now be downloaded here. This talk describes two different protocols for perfect simulation. The first, Partially Recursive Acceptance Rejection, gives an easy way to generate perfect samples from loosely coupled Markov random fields (such as the Ising model) in linear time without building a Markov chain at all for the problem.
The second part discusses Sequential Acceptance Rejection, a method that has proved useful for problems like approximating the permanent in dense problem instances.
Claremont Algebra/Number Theory/Combinatorics Seminar
Posted by markhuber in Invited Talks on November 1, 2011
Today I am giving the Algebra/Number Theory/Combinatorics Seminar at the Claremont Colleges. This talk, “What is a #P complete problem” is a prequel in a sense to an earlier talk I gave in the Seminar last year. In the earlier talk, I discussed new methods for approximating the permanent of a matrix. In this talk, I will argue that finding the permanent is a hard problem. One way to characterize hardness of a numerical problem is the notion of number P problems, or #P for short. I will define #P problems and give Ben-Dor and Halevi’s 1993 proof that finding the permanent of a matrix is a #P hard problem, so if we could solve it quickly, any problem in #P could also be solved quickly.
Ready to give talk at UMSL
Posted by markhuber in Invited Talks on October 11, 2011
I’m excited to be giving the Math and CS Colloquium at UMSL this week. My talk is written and now I’m just trying to get all my reservations together in one spot. Since this is our Fall Break at CMC, I will be staying the weekend in St. Louis, and am looking forward to getting to know the city a little bit.
Talk in UCLA Statistics Department
Posted by markhuber in Invited Talks on September 7, 2011
I will be giving the Statistics Seminar at UCLA on October 18th. The talk is titled: ”Perfect simulation of repulsive point processes”.
Abstract Entities in competition for resources, such as towns in a country or trees in a forest, often are further apart from each other than would be predicted if their spatial distribution was independently uniform. Repulsive point processes are used to model such data, but rarely are these distributions given in closed form. Instead, they can be given as either an algorithmic model, or as a unnormalized density with respect to a spatial Poisson point process. In this talk I will show how to generate random samples exactly from an algorithmic setup called the Matérn Type III model, and from an unnormalized density called the Strauss model. Also, I will discuss effective ways to turn these samples into estimates using these models.
Talk at Greek Stochastics γ now posted
Posted by markhuber in Invited Talks, Uncategorized on August 26, 2011
The talk that I gave at Greek Stochastics γ has now been posted to the list of talks on my website here. The talk, entitled “The Paired Product Estimator for normalizing constants of Gibbs distribution” details a method for approximation of partition functions that is markedly faster than previously known methods.
Second issue of Journal of Humanistic Mathematics published
Posted by markhuber in Journal of Humanistic Mathematics, Uncategorized on August 2, 2011
The second issue of the Journal of Humanistic Mathematics is now online! As usual, it contains several great pieces about mathematicians doing mathematics, two book reviews, more poetry, and for the first time a short fiction piece. Many thanks to my coeditor Gizem Karaali, who did most of the work getting this issue out this last month. The issue can be accessed here.
Talk at Greek Stochastics gamma
Posted by markhuber in Contributed Talks on May 31, 2011
Today at 15:00 I am presenting a talk at the Greek Stochastics gamma conference. The topic is an improved version of approximation for the normalizing constant of a Gibbs distribution that requires a number of samples that is linear in the log of the normalizing constant. The title of the talk is “The Paired Product Estimator”.