UVA Probability Seminar
Wednesdays, 4:30 - 5:30pm
Kerchof 317
Organizers: Christian Gromoll, Tai Melcher, & Leonid Petrov
Mathematics Recent Seminars Other Seminars Maps & Directions

Fall 2014

3 Sep organizational meeting
24 Sep Leo Petrov* (joint with Algebra, meets at 3:30p)
Random tilings, representation theory and Macdonald processes I
1 Oct Leo Petrov* (joint with Algebra, meets at 3:30p)
Random tilings, representation theory and Macdonald processes II
3 Oct Leo Petrov* (joint with Algebra, meets 2-3p)
Random tilings, representation theory and Macdonald processes III
8 Oct Camelia Pop (U Penn)
Harnack inequalities for degenerate diffusions
29 Oct Xin Liu (Clemson)
Convergence of Value Functions for Controlled Subcritical Stochastic Networks
5 Nov Harry Crane (Rutgers)
11 Nov Andrei Martínez-Finkelshtein* (University of Almería, visiting Vanderbilt University); joint with Harmonic Analysis and PDE seminar, meets at 4pm
12 Nov Steve Pincus (joint with Statistics)
Higher Order Dangers and Precisely Constructed Taxa in Models of Randomness
18 Nov Ivan Corwin* (Columbia) meets 4-5p
3 Dec Rob Neel (Lehigh)
* please note time, date, and/or location change

Abstracts

Random tilings, representation theory and Macdonald processes I

Leo Petrov* (joint with Algebra, meets at 3:30p)

I will discuss random lozenge tilings of polygons, their representation-theoretic interpretation (including connections to the character theory of the infinite-dimensional unitary group), and how this circle of ideas leads to Macdonald processes. The latter give rise to other probabilistic models such as random polymers and similar interacting stochastic particle systems
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Harnack inequalities for degenerate diffusions

Camelia Pop (U Penn)

We study various probabilistic and analytical properties of a class of degenerate diffusion operators arising in Population Genetics, the so-called generalized Kimura diffusion operators. Our main results are a stochastic representation of weak solutions to a degenerate parabolic equation with singular lower-order coefficients, and the proof of the scale-invariant Harnack inequality for nonnegative solutions to the Kimura parabolic equation. The stochastic representation of solutions that we establish is a considerable generalization of the classical results on Feynman-Kac formulas concerning the assumptions on the degeneracy of the diffusion matrix, the boundedness of the drift coefficients, and on the a priori regularity of the weak solutions.
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Convergence of Value Functions for Controlled Subcritical Stochastic Networks

Xin Liu (Clemson)

In this talk, we study certain control problems for subcritical multiclass queueing networks. A multiclass queueing network $N$ consists of multiple classes of jobs and multiple servers. We assume that each class of jobs can only be served by one server, while each server could serve multiple classes of jobs. Such network is called subcritical if the traffic intensity at each server is not greater than 1. A server is called critical if its traffic intensity is equal to 1, and it is called strictly subcritical if its traffic intensity is strictly less than 1. Denote by $N_c$ the subnetwork consisting of the critical servers and the classes of jobs served by these servers. It is shown that the value function of the suitably scaled network control problem for the network $N$ converges to that of the diffusion control problem for a modified critical subnetwork that has the same dimension as $N_c$. Our result, in particular, shows how to reduce the dimension of the control problem for subcritical queueing networks, and also suggests a general strategy to construct near optimal controls.
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Higher Order Dangers and Precisely Constructed Taxa in Models of Randomness

Steve Pincus (joint with Statistics)

The certification, construction and delineation of individual, infinite length `random` sequences has been a longstanding, yet incompletely resolved problem. We address this topic via the study of normal numbers, which have often been viewed as reasonable proxies for randomness, given their limiting equidistribution of subblocks of all lengths. However, limitations arise within this perspective. First, we explicitly construct a normal number that satisfies the Law of the Iterated Logarithm (LIL), yet exhibits pairwise bias towards repeated values, rendering it inappropriate for any collection of random numbers. Accordingly, we deduce that the evaluation of higher order block dynamics, even beyond limiting equidistribution and fluctuational typicality, is imperative in proper evaluation of sequential `randomness`. Second, we develop several criteria motivated by classical theorems for symmetric random walks, which lead to algorithms for generating normal numbers that satisfy a variety of attributes for the series of initial partial sums, including rates of sign changes, patterns of return times to 0, and the extent of fairness of the sequence. Such characteristics are generally unaddressed in most evaluations of `randomness`. More broadly, we can differentiate normal numbers both on the basis of multiple distinct qualitative attributes, as well as quantitatively via a spectrum of rates within each attribute. Furthermore, we exhibit a toolkit of techniques to construct normal sequences that realize diverse a priori specifications, including profound biases. Overall, we elucidate the vast diversity within the category of normal sequences.
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Mathematics Recent Seminars Other Seminars Maps & Directions