[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.
