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Upcoming Educational Events

  1. Summer Graduate School Recent topics on well-posedness and stability of incompressible fluid and related topics

    Organizers: LEAD Yoshikazu Giga (University of Tokyo), Maria Schonbek (University of California, Santa Cruz), Tsuyoshi Yoneda (University of Tokyo)
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    Fluid-flow stream function color-coded by vorticity in 3D flat torus calculated by K. Nakai (The University of Tokyo)

    The purpose of the workshop is to introduce graduate students to fundamental results on the Navier-Stokes and the Euler equations, with special emphasis on the solvability of its initial value problem with rough initial data as well as the large time behavior of a solution. These topics have long research history. However, recent studies clarify the problems from a broad point of view, not only from analysis but also from detailed studies of orbit of the flow.

    Updated on Jan 10, 2019 09:13 AM PST
  2. Summer Graduate School Toric Varieties

    Organizers: David Cox (Amherst College), Henry Schenck (Iowa State University)
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    This simplicial fan in 3-dimensional space

    Toric varieties are algebraic varieties defined by combinatorial data, and there is a wonderful interplay between algebra, combinatorics and geometry involved in their study. Many of the key concepts of abstract algebraic geometry (for example, constructing a variety by gluing affine pieces) have very concrete interpretations in the toric case, making toric varieties an ideal tool for introducing students to abstruse concepts.

    Updated on Sep 21, 2018 04:02 PM PDT
  3. Summer Graduate School H-Principle

    Organizers: LEAD Emmy Murphy (Northwestern University), Takashi Tsuboi (University of Tokyo)
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    The image of a large sphere isometrically embedded into a small space through a C^1 embedding. (Attributions: E. Bartzos, V. Borrelli, R. Denis, F. Lazarus, D. Rohmer, B. Thibert)

    This two week summer school will introduce graduate students to the theory of h-principles.  After building up the theory from basic smooth topology, we will focus on more recent developments of the theory, particularly applications to symplectic and contact geometry, fluid dynamics, and foliation theory.

    Updated on Sep 21, 2018 04:02 PM PDT
  4. Summer Graduate School Mathematics of Machine Learning

    Organizers: Sebastien Bubeck (Microsoft Research), Anna Karlin (University of Washington), Adith Swaminathan (Microsoft Research)
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    Popular visualization of the MNIST dataset

    Learning theory is a rich field at the intersection of statistics, probability, computer science, and optimization. Over the last decades the statistical learning approach has been successfully applied to many problems of great interest, such as bioinformatics, computer vision, speech processing, robotics, and information retrieval. These impressive successes relied crucially on the mathematical foundation of statistical learning.

    Recently, deep neural networks have demonstrated stunning empirical results across many applications like vision, natural language processing, and reinforcement learning. The field is now booming with new mathematical problems, and in particular, the challenge of providing theoretical foundations for deep learning techniques is still largely open. On the other hand, learning theory already has a rich history, with many beautiful connections to various areas of mathematics (e.g., probability theory, high dimensional geometry, game theory). The purpose of the summer school is to introduce graduate students (and advanced undergraduates) to these foundational results, as well as to expose them to the new and exciting modern challenges that arise in deep learning and reinforcement learning.

    Updated on Jul 15, 2019 09:25 AM PDT
  5. Workshop Modern Math Workshop 2019

    Organizers: Elvan Ceyhan (SAMSI - Statistical and Applied Mathematical Sciences Institute), Christian Ratsch (University of California, Los Angeles; Institute of Pure and Applied Mathematics (IPAM)), Michael Singer (MSRI - Mathematical Sciences Research Institute), Ulrica Wilson (Morehouse College; Institute for Computational and Experimental Research in Mathematics (ICERM))
    Mmw2016

    As part of the Mathematical Sciences Collaborative Diversity Initiatives, six mathematics institutes are pleased to host their annual SACNAS pre-conference event, the 2019 Modern Math Workshop (MMW). The Modern Math Workshop is intended to encourage minority undergraduates to pursue careers in the mathematical sciences and to assist undergraduates, graduate students and recent PhDs in building their research networks.

    Updated on May 16, 2019 05:33 PM PDT