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Anusha Krishnan, Syracuse University, Prescribing Ricci curvature on a product of spheres

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The Ricci curvature Ric(g) is a symmetric 2-tensor on a Riemannian manifold (M,g) that encodes curvature information. It features in several interesting geometric PDEs such as the Ricci flow and the Einstein equation. The nature of Ric(g) as a differential operator -- nonlinear and degenerate elliptic -- make these equations particularly challenging. Host: Peter McGrath Instructions to join: Zoom…

Tracie Ellis, SIAM Mathematics in Industry Seminar

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Zoom link: https://ncsu.zoom.us/j/96495890729?pwd=VUhKZWFKbXBGLy9LVjlJalRsL2RBdz09 Passcode: SIAM Abstract: Join Tracie Ellis, Vice President Business Analytics at Bandwidth, for an informal discussion about her team’s role in creating a data-driven culture at Bandwidth, a software/telecommunications company on Centennial Campus. Tracie will share a bit of background about the company, their data evolution and the qualifications and experience of the Analytics…

‪Theresa Anderson, Purdue University, Dyadic analysis (virtually) meets number theory

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In this talk we discuss two ways in which dyadic analysis and number theory share a rich interaction. The first involves a complete classification of "distinct dyadic systems". These are sets of grids which allow one to compare any Euclidean ball nicely with any dyadic cube, and allow for showing that a large number of…

Silvia Gazzola, University of Bath, Iterative regularization methods for large-scale linear inverse problems

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 Inverse problems are ubiquitous in many areas of Science and Engineering and, once discretized, they lead to ill-conditioned linear systems, often of huge dimensions: regularization consists in replacing the original system by a nearby problem with better numerical properties, in order to find a meaningful approximation of its solution. After briefly surveying some standard regularization…

Joonas Ilmavirta, Tampere University, Finland, The light ray transform

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When is a function in the spacetime uniquely determined by its integrals over all light rays? I will introduce the problem, discuss why we might care about it, and how one might go about proving such uniqueness results. Depending on time and audience interest, I can also discuss proofs and tensor tomography.   Organizer: T.…

Victor Magron, LAAS-CNRS, France, The quest of efficiency and certification in polynomial optimization

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In 2001, Lasserre introduced a nowadays famous hierarchy of relaxations, called the moment-sums of squares hierarchy, allowing one to obtain a converging sequence of lower bounds for the minimum of a polynomial over a compact semialgebraic set. Each lower bound is computed by solving a semidefinite program (SDP). There are two common drawbacks related to…

Samantha Kirk, NC State, How to Construct Representations of Twisted Toroidal Lie Algebras via Lattice Vertex Algebras

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If you take a simple finite-dimensional Lie algebra g and tensor it with the Laurent polynomials in one variable, then you will get an infinite-dimensional Lie algebra known as a loop algebra. Affine Lie algebras are the central extensions of such loop algebras and their representations have been of interest to several mathematicians. What happens if we tensor g with…

Lars Ruthotto, Emory University, Numerical Analysis Perspectives on Deep Neural Networks

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The resurging interest in deep learning is commonly attributed to advances in hardware and growing data sizes and less so to new algorithmic improvements. However, cutting-edge numerical methods are needed to tackle ever larger and more complex learning problems. In this talk, I will illustrate numerical analysis tools for improving the effectiveness of deep learning…

Roberto Cominetti, Universidad Adolfo Ibáñez, Chile, Convergence rates for Krasnoselskii-Mann fixed-point iterations

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A popular method to approximate a fixed point of a non-expansive map is C is the Krasnoselskii-Mann iteration. This covers a wide range of iterative methods in convex minimization, equilibria, and beyond. In the Euclidean setting, a flexible method to obtain convergence rates for this iteration is the PEP methodology introduced by Drori and Teboulle…