Refreshments are served 30 minutes before each talk in the Conference Room MSPB 335
|Wednesday, October 24, 2018 at 6:00 p.m. in the Marx Library Auditorium (refreshments
and snacks will be served at 5:30 p.m. in room 181 of the Marx Library)
This talk is aimed at a general audience!
|Nagaraj Neerchal, University of Maryland, Baltimore County (UMBC)
Fifth Satya Mishra Memorial Lecture
The Statistical Modeling of Self-Reported and Proxy Observations in Longitudinal Studies
Abstract: In gerontological studies when the patients become unable to provide responses by themselves due to advancing severity of their conditions, proxy responses by a relative or a caregiver “proxy” are used. The resulting database contains both self- reported as well as proxy observations for the same subject at different time points. Some statistical models are being investigated that can analyze self-reported and proxy observations together so that relevant parameters and their standard errors can be estimated in a single framework. This is joint work with Mina Hosseini, UMBC, and Dr. Ann Gruber-Baldini, School of Public Health, University of Maryland, Baltimore.
|Thursday, October 25, 2018 at 3:30 p.m. in MSPB 370||Nagaraj Neerchal, University of Maryland, Baltimore County (UMBC)||
Prediction Methods for Semi-Continuous Data with Applications in Climate Science
Abstract: Semi-continuous random variables have discrete and continuous components with support on a set of discrete points and a subset on the real line. Daily precipitation (rainfall) data is an example of such a random variable with a point mass at 0 and an absolutely continuous distribution function on the positive real line. When the Probability of observing a 0 is assumed to be independent of the parameters of the continuous part, the density of the random variable takes the form a Two-Part model. A popular form that enforces a dependency is the standard Tobit model. We briefly review some inferential aspects of the semi-continuous distributions and present several methods of prediction and derivation of predictive densities, motivated by applications of spatio-temporal models in Climate Science. This is joint work with Sai Kumar Popuri, UMBC, and Dr. Amita Mehta of Joint Center for Earth Systems Technology.
|Tuesday, October 30, 2018 at 3:30 p.m. in MSPB 370
Note the different day!
|Andrew Owens, Auburn University||
Rainbow Cycles on Complete Graphs
Abstract: It is well known that a complete graph on n vertices can be edge colored with n-1 colors in order to avoid rainbow cycles. No such coloring exists using n colors. A certain encoding of full binary trees produces edge colorings using this maximum number of colors, n-1, in order to avoid rainbow cycles. Interestingly, all such colorings can be formed using this encoding. A few years later a similar result was found to hold for complete bipartite graphs and, subsequently, complete multipartite graphs. Most recently, an analogous theorem was found for all general connected graphs. First, we will look at the connection between these edge colorings and full binary trees; we then will highlight some of the important ideas used in order to prove the general case.
|Thursday, November 8, 2018 at 3:30 p.m. in MSPB 370||Elena Pavelescu, University of South Alabama||
Escher Squares and Lattice Links
|Thursday, November 15, 2018 at 3:30 p.m. in MSPB 370||Larry Rolen, Vanderbilt University||
Jensen-Pólya Criterion for the Riemann Hypothesis and Related Problems
Abstract: In this talk, I will summarize forthcoming work with Griffin, Ono, and Zagier. In 1927 Pólya proved that the Riemann Hypothesis is equivalent to the hyperbolicity of Jensen polynomials for Riemann's Xi-function. This hyperbolicity has been proved for degrees less than or equal to 3. We obtain an arbitrary precision asymptotic formula for the derivatives of Xi, which allows us to prove the hyperbolicity of 100% of the Jensen polynomials of each degree. We obtain a general theorem which models such polynomials by Hermite polynomials. In the case of Riemann's Xi-function, this proves the GUE random matrix model prediction for the distribution of zeros in derivative aspect. This general condition also confirms a conjecture of Chen, Jia, and Wang on the partition function.
|Tuesday, December 4, 2018 at 3:30 p.m. in MSPB 370
Note the different day!
|Katherine Perry, University of Denver||
Rainbow Spanning Trees in Edge-Colored Complete Graphs
Abstract: A spanning tree of an edge-colored graph is rainbow provided that each of its edges receives a distinct color. In 1996, Brualdi and Hollingsworth conjectured that if K2m is properly (2m − 1)-edge-colored, then the edges of K2m can be partitioned into m rainbow spanning trees, except when m = 2. In this talk, we’ll look at the history and recent results concerning this conjecture and consider the extremal question of maximizing and minimizing the number of rainbow spanning trees in Kn, given a special type of (n − 1)-edge-coloring which is surjective and rainbow cycle free, called a JL-coloring.
|October 18, 2018||Qiyu Sun, University of Central Florida||
Wiener’s Lemma and Beyond
Abstract: The classical Wiener’s lemma states that if f(x) is a function with an absolutely convergent Fourier series, which nowhere vanishes for real arguments, 1/f(x) has an absolutely convergent Fourier series. In this talk, I will discuss various aspects of Wiener’s lemma from reciprocal of periodic functions to inverse of matrices and to inverse functions, and their applications to spectral invariance of integral operators and signal processing on spatially distributed networks.
|September 20, 2018||Bin Wang, University of South Alabama||
A New Procedure to Detect Differentially Expressed Genes from NGS-seq Data
Abstract: Gene expressions profiled using next generation sequencing techniques are highly discretized and have a lot of zeros. This poses difficulties to modeling the NGS gene expression data. Based on a two-component measurement error model, we propose to model the NGS gene expression data using finite mixture models and fit the distributions using an EM-algorithm via data binning. The applications of the proposed methods will be illustrated through a real TCGA lung cancer dataset and benchmarked with existing methods in CRAN R package edgeR.
|September 13, 2018||Christine Lee, University of South Alabama||
Stability and Triviality of Plamenevskaya’s Transverse Invariant from Khovanov Homology
Abstract: We prove a stability property of Plamenevskaya’s transverse invariant from Khovanov homology, and use it to give several families of examples of 3-6 braids for which the invariant may be used to detect non quasi-positivity and non right-veeringness. We also construct an infinite family of pretzel knots for which Plamenevskaya’s invariant vanishes for every single transverse link representative from a braid representative. This is joint work with Diana Hubbard.