AMS Sectional Meeting AMS Special Session

Current as of Saturday, March 26, 2022 03:30:04

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• Virtual Program
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• Program
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• Deadlines
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• Timetable
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• Chronological Index of Talks
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• Registration/Etc.


• Inquiries: meet@ams.org

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Spring Eastern Virtual Sectional Meeting (formerly at Tufts University)

• now meeting virtually, EDT (hosted by the American Mathematical Society), Virtual, RI
• March 19-20, 2022 (Saturday - Sunday)
• Meeting #1176

Associate Secretary for the AMS Scientific Program:

Steven H Weintraub, AMS shw2@lehigh.edu

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Special Session on Mathematics of Data Science

• Saturday March 19, 2022, 8:00 a.m.-10:45 a.m.
  Special Session on Mathematics of Data Science, I
  Special Session 2, American Mathematical Society
  Organizers:
  Anna Haensch, Tufts University
  Vasileios Maroulas, University of Tennessee Knoxville
  James M. Murphy, Tufts University jm.murphy@tufts.edu
  Abani Patra, Tufts University
  Abiy Tasissa, Tufts University
  

  • 8:00 a.m.
    Geometric averages of redistricting plans and clustered datasets.
    Tom Needham, Florida State University
    Thomas Weighill*, University of North Carolina at Greensboro
    (1176-51-59)
  • 8:30 a.m.
    Principled Data Manipulation with Optimal Transport.
    David Alvarez-Melis*, Microsoft Research
    (1176-68-129)
  • 9:00 a.m.
    Multiscale Models for Sparsity Constrained Data Reduction.
    Prashant Shekhar*, Embry-Riddle Aeronautical University
    Abani Patra, Tufts University
    (1176-41-153)
  • 9:30 a.m.
    A reference-based Bayesian method for sample-specific complete deconvolution.
    Kai Kang*, Massachusetts Institute of Technology
    (1176-62-246)
  • 10:00 a.m.
    Group equivariant machine learning.
    Soledad Villar*, Johns Hopkins University
    (1176-90-260)
• Saturday March 19, 2022, 3:00 p.m.-5:45 p.m.
  Special Session on Mathematics of Data Science, II
  Special Session 2, American Mathematical Society
  Organizers:
  Anna Haensch, Tufts University
  Vasileios Maroulas, University of Tennessee Knoxville
  James M. Murphy, Tufts University jm.murphy@tufts.edu
  Abani Patra, Tufts University
  Abiy Tasissa, Tufts University
  

  • 3:00 p.m.
    Decomposing Low-Rank Symmetric Tensors.
    Joe Kileel*, University of Texas at Austin
    (1176-65-313)
  • 3:30 p.m.
    Efficient distribution classification via optimal transport embeddings.
    Caroline Moosmueller*, University of California San Diego
    Alexander Cloninger, University of California San Diego
    (1176-65-64)
  • 4:00 p.m.
    The Dirichlet-to-Neumann operator and data.
    Wesley Hamilton*, University of Utah
    (1176-35-187)
  • 4:30 p.m.
    Bayesian Inference with Random Persistence Diagrams.
    Austin Lawson*, University of Tennessee
    Vasileios Maroulas, University of Tennessee
    Farzana Nasrin, University of Hawaii
    Theodore Papamarkou, University of Manchester
    (1176-62-226)
  • 5:00 p.m.
    Finding shortest loop bases and the decomposition of the higher-order homology embeddings.
    Yu-Chia Chen, Meta, Inc.
    Marina Meila*, University of Washington
    Ioannis Kevrekidis, Johns Hopkins University
    (1176-57-355)
• Sunday March 20, 2022, 8:30 a.m.-10:20 a.m.
  Special Session on Mathematics of Data Science, III
  Special Session 2, American Mathematical Society
  Organizers:
  Anna Haensch, Tufts University
  Vasileios Maroulas, University of Tennessee Knoxville
  James M. Murphy, Tufts University jm.murphy@tufts.edu
  Abani Patra, Tufts University
  Abiy Tasissa, Tufts University
  

  • 8:30 a.m.
    An Efficient Adaptive Sampling Deep Learning Galerkin Method.
    Andreas C Aristotelous*, The University of Akron
    Edward C Mitchell, The University of Tennessee, Knoxville
    Vasileios Maroulas, The University of Tennessee, Knoxville
    (1176-65-130)
  • 9:00 a.m.
    Modeling the spread of COVID-related beliefs.
    Nicholas Rabb*, Tufts University
    Lenore Cowen, Tufts University
    Jan P. de Ruiter, Tufts University
    Matthias Scheutz, Tufts University
    (1176-91-73)
  • 9:30 a.m.
    Revisiting the Effect Size Analogue for Variable Selection in Nonlinear Regression.
    Emily T Winn*, Brown University
    Maryclare Griffin, University of Massachusetts Amherst
    Lorin Crawford, Microsoft Research New England
    (1176-62-31)
  • 10:00 a.m.
    Simple, mechanism-based statistical models provide powerful tools for understanding microbial communities.
    Collin B. Edwards*, Tufts University, University of Washington, Vancouver
    Brooke Anderson, University of California, San Diego
    Rachel J. Dutton, University of California, San Diego
    Benjamin E. Wolfe, Tufts University
    (1176-92-359)

Inquiries: meet@ams.org

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