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[01822] Domain decomposition for the Random Feature Method

  • Session Time & Room : 5C (Aug.25, 13:20-15:00) @E705
  • Type : Contributed Talk
  • Abstract : The random feature method (RFM) is a framework for solving PDEs sharing the merits of both traditional and machine learning-based algorithms. The direct method for optimization shows a high accuracy but faces acute memory and time-consuming issues with the increase of the scale of the problem. We introduced the domain decomposition into RFM and build a distributed, low-communication, and high-parallelism framework which relieves the pressure of storage and improves solving efficiency significantly in RFM.
  • Classification : 65N99, 65F20, 65-04, 65Y05
  • Format : Talk at Waseda University
  • Author(s) :
    • Yifei Sun (Soochow University)
    • Jingrun Chen (University of Science and Technology of China)
    • Weinan E (Peking University)