Seminars and Colloquia by Series

Monday, March 12, 2018 - 11:15 , Location: skiles 005 , Giuseppe Genovese , University of Zurich , Organizer: Livia Corsi
The derivative nonlinear Schrödinger equation (DNLS) is an integrable, mass-critical PDE. The integrals of motion may be written as an infinite sequence of functionals on Sobolev spaces of increasing regularity. I will show how to associate to them a family of invariant Gibbs measures, if the L^2 norm of the solution is sufficiently small (mass-criticality). A joint work with R. Lucà (Basel) and D. Valeri (Beijing).
Monday, March 12, 2018 - 10:00 , Location: Klaus 2108 , Rundong Du , Georgia Tech , , Organizer: Mohammad Ghomi
Constrained low rank approximation is a general framework for data analysis, which usually has the advantage of being simple, fast, scalable and domain general. One of the most known constrained low rank approximation method is nonnegative matrix factorization (NMF). This research studies the design and implementation of several variants of NMF for text, graph and hybrid data analytics. It will address challenges including solving new data analytics problems and improving the scalability of existing NMF algorithms. There are two major types of matrix representation of data: feature-data matrix and similarity matrix. Previous work showed successful application of standard NMF for feature-data matrix to areas such as text mining and image analysis, and Symmetric NMF (SymNMF) for similarity matrix to areas such as graph clustering and community detection. In this work, a divide-and-conquer strategy is applied to both methods to improve their time complexity from cubic growth with respect to the reduced low rank to linear growth, resulting in DC-NMF and HierSymNMF2 method. Extensive experiments on large scale real world data shows improved performance of these two methods.Furthermore, in this work NMF and SymNMF are combined into one formulation called JointNMF, to analyze hybrid data that contains both text content and connection structure information. Typical hybrid data where JointNMF can be applied includes paper/patent data where there are citation connections among content and email data where the sender/receipts relation is represented by a hypergraph and the email content is associated with hypergraph edges.  An additional capability of the JointNMF is prediction of unknown network information which is illustrated using several real world problems such as citation recommendations of papers and activity/leader detection in organizations.The dissertation also includes brief discussions of relationship among different variants of NMF.
Series: Other Talks
Sunday, March 11, 2018 - 16:00 , Location: Drew Charter School , various performers , GT, Emory, Little Minute , Organizer:
This is an Atlanta Science Festival performance in which mathematicians team up with dancers to give an artistic interpretation to the public of some mathematicians and some mathematical concepts.  This year's show will have an emphasis on graph theory.  There will be two performances at Drew Charter School in East Atlanta.  For tickets go to or .
Friday, March 9, 2018 - 15:00 , Location: Skiles 006 , Evangelos Theodorou , GT AE , Organizer: Sung Ha Kang
In this talk I will present an information theoretic approach to stochastic optimal control and inference  that has advantages  over classical methodologies and theories for decision making under uncertainty.  The main idea  is that there are certain connections between optimality principles in control and information theoretic inequalities in statistical physics that allow  us to solve hard decision making problems in robotics, autonomous systems and beyond. There are essentially two different points of view  of the same "thing" and these two different points of view  overlap   for a fairly general class of dynamical systems that undergo stochastic effects.  I will also present a holistic view of autonomy that collapses planning, perception and control into one computational engine, and ask questions  such as  how organization and structure relates to computation and performance. The last part of my talk includes computational frameworks for uncertainty representation   and suggests ways to incorporate these representations within decision making and control.
Friday, March 9, 2018 - 14:00 , Location: Skiles 006 , Jen Hom , Georgia Tech , Organizer: Jennifer Hom
In this series of talks, we will study the relationship between the Alexander module and the bordered Floer homology of the Seifert surface complement. In particular, we will show that bordered Floer categorifies Donaldson's TQFT description of the Alexander module. This seminar will be an hour long to allow for the GT-MAP seminar at 3 pm.
Friday, March 9, 2018 - 10:00 , Location: Skiles 006 , Kisun Lee , Georgia Tech , , Organizer: Kisun Lee
This is an intoductory talk for the currently using methods for certifying roots for system of equations. First we discuss about alpha-theory which was constructed by Smale and Shub, and explain how this theory could be modified in order to apply in actual problems. In this step, we point out that alpha theory is still restricted only into polynomial systems and polynomial-exponential systems. After that as a remedy for this problem, we will introduce an interval arithmetic, and the Krawczyk method. We will end the talk with a discussion about how these current methods could be used in more general setting.
Thursday, March 8, 2018 - 15:05 , Location: Skiles 006 , Jan Rosinski , University of Tennessee , , Organizer: Michael Damron
We obtain an extension of the Ito-Nisio theorem to certain non separable Banach spaces and apply it to the continuity of the Ito map and Levy processes.  The Ito map assigns a rough path input of an ODE to its solution (output). Continuity of this map usually requires strong, non separable, Banach space norms on the path space. We consider as an input to this map a series expansion a Levy process and study the mode of convergence of the corresponding series of outputs. The key to this approach is the validity of Ito-Nisio theorem in non separable Wiener spaces of certain functions of bounded p-variation. This talk is based on a joint work with Andreas Basse-O’Connor and Jorgen Hoffmann-Jorgensen.
Thursday, March 8, 2018 - 13:30 , Location: Skiles 005 , Alexander Hoyer , Math, GT , Organizer: Robin Thomas
For a graph G, a set of subtrees of G are edge-independent with root r ∈ V(G) if, for every vertex v ∈ V(G), the paths between v and r in each tree are edge-disjoint. A set of k such trees represent a set of redundant broadcasts from r which can withstand k-1 edge failures. It is easy to see that k-edge-connectivity is a necessary condition for the existence of a set of k edge-independent spanning trees for all possible roots. Itai and Rodeh have conjectured that this condition is also sufficient. This had previously been proven for k=2, 3. We prove the case k=4 using a decomposition of the graph similar to an ear decomposition. Joint work with Robin Thomas.
Wednesday, March 7, 2018 - 14:00 , Location: Atlanta , Agniva Roy , GaTech , Organizer: Anubhav Mukherjee
Three dimensional lens spaces L(p,q) are well known as the first examples of 3-manifolds that were not known by their homology or fundamental group alone. The complete classification of L(p,q), upto homeomorphism, was an important result, the first proof of which was given by Reidemeister in the 1930s. In the 1980s, a more topological proof was given by Bonahon and Hodgson. This talk will discuss two equivalent definitions of Lens spaces, some of their well known properties, and then sketch the idea of Bonahon and Hodgson's proof. Time permitting, we shall also see Bonahon's result about the mapping class group of L(p,q).
Wednesday, March 7, 2018 - 11:00 , Location: Skiles 005 , Adam Marcus , Princeton University , , Organizer: Galyna Livshyts
 I will discuss a recent line of research that uses properties of real rooted polynomials to get quantitative estimates in combinatorial linear algebra problems.  I will start by discussing the main result that bridges the two areas (the "method of interlacing polynomials") and show some examples of where it has been used successfully (e.g. Ramanujan families and the Kadison Singer problem). I will then discuss some more recent work that attempts to make the method more accessible by providing generic tools and also attempts to explain the accuracy of the method by linking it to random matrix theory and (in particular) free probability.  I will end by mentioning some current research initiatives as well as possible future directions.