BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Mathematics - ECPv4.8.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Mathematics
X-ORIGINAL-URL:https://math.ua.edu
X-WR-CALDESC:Events for Mathematics
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20190401T110000
DTEND;TZID=America/Chicago:20190401T120000
DTSTAMP:20190424T061647
CREATED:20190227T173317Z
LAST-MODIFIED:20190329T162935Z
UID:3814-1554116400-1554120000@math.ua.edu
SUMMARY:Analysis Seminar - Ryan Berndt\, Otterbein University
DESCRIPTION:Title: Two-weight problem for the Fourier transform. \nAbstract: We examine the problem of the Fourier transform mapping one weighted Lebesgue space into another\, by studying necessary conditions and sufficient conditions which expose an underlying geometry. In the necessary conditions\, this geometry is connected to an old result of Mahler concerning the the measure of a convex body and its geometric polar being essentially reciprocal. An additional assumption\, that the weights must belong to a reverse Hölder class\, is used to formulate the sufficient condition. \n
URL:https://math.ua.edu/event/analysis-seminar-4/
LOCATION:346 Gordon Palmer Hall
CATEGORIES:Analysis Seminar,Math Department
ORGANIZER;CN="Kabe%20Moen":MAILTO:kabe.moen at ua.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20190408T110000
DTEND;TZID=America/Chicago:20190408T120000
DTSTAMP:20190424T061647
CREATED:20190227T173408Z
LAST-MODIFIED:20190227T173408Z
UID:3816-1554721200-1554724800@math.ua.edu
SUMMARY:Analysis Seminar - Khalid Said\, University of Alabama
DESCRIPTION:
URL:https://math.ua.edu/event/analysis-seminar-khalid-said-university-of-alabama/
LOCATION:346 Gordon Palmer Hall
CATEGORIES:Analysis Seminar,Math Department
ORGANIZER;CN="Kabe%20Moen":MAILTO:kabe.moen at ua.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20190409T110000
DTEND;TZID=America/Chicago:20190409T130000
DTSTAMP:20190424T061647
CREATED:20190401T142945Z
LAST-MODIFIED:20190401T154033Z
UID:3886-1554807600-1554814800@math.ua.edu
SUMMARY:Colloquium - Mark Behrens\, University of Notre Dame
DESCRIPTION:Title: “Current themes in the study of the homotopy groups of spheres” \nAbstract: I will summarize the current state of affairs of the study of the stable homotopy groups of spheres\, and will describe some connections to algebraic and differential geometry. \n
URL:https://math.ua.edu/event/colloquium-mark-behrens-university-of-notre-dame/
LOCATION:346 Gordon Palmer Hall
CATEGORIES:Colloquium,Math Department
ORGANIZER;CN="Bulent%20Tosun":MAILTO:btosun@ua.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20190412T110000
DTEND;TZID=America/Chicago:20190412T120000
DTSTAMP:20190424T061647
CREATED:20190409T212246Z
LAST-MODIFIED:20190409T212621Z
UID:3900-1555066800-1555070400@math.ua.edu
SUMMARY:Applied Math Seminar - Rongjie Lai\, Rensselaer Polytechnic Institute
DESCRIPTION:Title: Understanding Manifold-structured Data via Geometric Modeling and Learning \nAbstract: Analyzing and inferring the underlying global intrinsic structures of data from its local information are critical in many fields. In practice\, coherent structures of data allow us to model data as low dimensional manifolds\, represented as point clouds\, in a possible high dimensional space. Different from image and signal processing which handle functions on flat domains with well-developed tools for processing and learning\, manifold-structured data sets are far more challenging due to their complicated geometry and representation ambiguities. To overcome these ambiguities\, I will first discuss modeling based methods. This approach uses geometric PDEs to adapt the intrinsic manifolds structure of data and extracts various invariant descriptors to characterize and understand data through solutions of differential equations on manifolds. Inspired by recent developments of deep learning\, I will also discuss our recent work of a new way of defining convolution on manifolds and demonstrate its potential to conduct geometric deep learning on manifolds. This geometric way of defining convolution provides a natural combination of modeling and learning on manifolds. It enables further applications in comparing\, classifying and understanding manifold-structured data by combing with recent advances in deep learning. \n
URL:https://math.ua.edu/event/applied-math-seminar-rongjie-lai-rensselaer-polytechnic-institute/
LOCATION:346 Gordon Palmer Hall
CATEGORIES:Applied Math Seminar,Math Department
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20190419T110000
DTEND;TZID=America/Chicago:20190419T120000
DTSTAMP:20190424T061647
CREATED:20190416T200200Z
LAST-MODIFIED:20190416T200622Z
UID:3908-1555671600-1555675200@math.ua.edu
SUMMARY:Applied Math Seminar - Trang Dinh\, University of Alabama
DESCRIPTION:Title: Understanding Tensor and Tensor Decompositions \nAbstract: Tensors are multidimensional arrays that can play a key role in the representation of big data. Decompositions of higher-order tensors have applications in biochemistry\, signal processing\, data mining\, neuroscience\, and elsewhere. The talk will present commonly used tensor operations and different types of tensor decomposition. Specifically\, it will illustrate the CANDECOMP/PARAFAC (CP) decomposition and the Tucker decomposition\, which are examples of decompositions that have been employed to optimize the storage of large high-order tensors that arise naturally in different scientific fields. Computation with the decomposed tensors\, however\, is still an actively growing field of research that promises to offer new insights into solving classic problems in numerical analysis. \n
URL:https://math.ua.edu/event/applied-math-seminar-trang-dinh-university-of-alabama/
LOCATION:346 Gordon Palmer Hall
CATEGORIES:Applied Math Seminar,Math Department
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20190423T110000
DTEND;TZID=America/Chicago:20190423T120000
DTSTAMP:20190424T061647
CREATED:20190108T204713Z
LAST-MODIFIED:20190418T133405Z
UID:3691-1556017200-1556020800@math.ua.edu
SUMMARY:Colloquium - Xiaofan Li\, Illinois Institute of Technology
DESCRIPTION:Title: Numerical simulations of macroscopic quantities for stochastic differential equations with alpha-stable processes \nAbstract: The mean first exit time\, escape probability and transitional probability density are utilized to quantify dynamical behaviors of stochastic differential equations with non-Gaussian\, $\alpha$-stable type L\’evy motions. Taking advantage of the Toeplitz matrix structure of the time-space discretization\, a fast and accurate numerical algorithm is proposed to simulate the nonlocal Fokker-Planck equations on either a bounded or infinite domain. Under a specified condition\, the scheme is shown to satisfy a discrete maximum principle and to be convergent. \n
URL:https://math.ua.edu/event/colloquium-xiaofan-li-illinois-institute-of-technology/
LOCATION:346 Gordon Palmer Hall
CATEGORIES:Colloquium,Math Department
ORGANIZER;CN="Shan%20Zhao":MAILTO:szhao@ua.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20190429T110000
DTEND;TZID=America/Chicago:20190429T120000
DTSTAMP:20190424T061647
CREATED:20190227T173456Z
LAST-MODIFIED:20190227T173456Z
UID:3818-1556535600-1556539200@math.ua.edu
SUMMARY:Analysis Seminar
DESCRIPTION:
URL:https://math.ua.edu/event/analysis-seminar-5/
LOCATION:346 Gordon Palmer Hall
CATEGORIES:Analysis Seminar,Math Department
ORGANIZER;CN="Kabe%20Moen":MAILTO:kabe.moen at ua.edu
END:VEVENT
END:VCALENDAR