Registered Data

[00389] Randomized methods for solving linear systems and eigenvalue problems

  • Session Date & Time :
    • 00389 (1/3) : 2C (Aug.22, 13:20-15:00)
    • 00389 (2/3) : 2D (Aug.22, 15:30-17:10)
    • 00389 (3/3) : 2E (Aug.22, 17:40-19:20)
  • Type : Proposal of Minisymposium
  • Abstract : Although the field of randomized numerical linear algebra has grown significantly, developments on accurate randomized solvers only start to emerge in recent years. This minisymposium intends to bring together researchers to exchange ideas on producing fast and accurate randomized solvers, studying their performance, and exploring new applications. We will specifically focus on randomized methods for solving linear systems and eigenvalue problems and on randomized strategies that can produce reliable high-quality solutions or approximations. Some topics include randomized iterative solvers, preconditioning, matrix approximations, low-rank compression, and eigenvalue detection. Applications to PDE solutions, machine learning, and data analysis will also be discussed.
  • Organizer(s) : Jianlin Xia, Qiang Ye
  • Classification : 68W20, 65F05, 65F08, 65F15, 65F55
  • Speakers Info :
    • Jianlin Xia (Purdue University)
    • Ming Gu (UC Berkeley)
    • Victor Pan (CUNY Lehman)
    • Arvind Saibaba (North Carolina State University)
    • Laura Grigori (Inria)
    • Sabine Le Borne (Technische Universitat Hamburg)
    • Zhongyuan Chen (Purdue University)
    • Yuji Nakatsukasa (University of Oxford)
    • Qiang Ye (University of Kentucky)
    • David Woodruff (Carnegie Mellon University)
    • Mateo Diaz (Johns Hopkins University)
    • Diana Halikias (Cornell University)
  • Talks in Minisymposium :