On convergence of greedy block nonlinear Kaczmarz methods with momentum
By: Naiyu Jiang , Wendi Bao , Lili Xing and more
Potential Business Impact:
Solves hard math problems faster with a new trick.
In this paper, for solving nonlinear systems we propose two pseudoinverse-free greedy block methods with momentum by combining the residual-based weighted nonlinear Kaczmarz and heavy ball methods. Without the full column rank assumptions on Jacobi matrices of nonlinear systems, we provide a thorough convergence analysis, and derive upper bounds for the convergence rates of the new methods. Numerical experiments demonstrate that the proposed methods with momentum are much more effective than the existing ones.
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