Anderson Acceleration for Nonsmooth Fixed Point Problems
Wei Bian, Xiaojun Chen
Harbin Institute of Technology Hong Kong Polytechnic University
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摘要与影响
We give new convergence results of Anderson acceleration for the composite $\max$ fixed point problem. We prove that Anderson(1) and EDIIS(1) are q-linear convergent with a smaller q-factor than existing q-factors. Moreover, we propose a smoothing approximation of the composite max function in the contractive fixed point problem. We show that the smoothing approximation is a contraction mapping with the same fixed point as the composite $\max$ fixed point problem. Our results rigorously confirm that the nonsmoothness does not affect the convergence rate of the Anderson acceleration method when we use the proposed smoothing approximation for the composite $\max$ fixed point problem. Numerical results for constrained minimax problems, complementarity problems, and nonsmooth differential equations are presented to show the efficiency and good performance of the proposed Anderson acceleration method with smoothing approximation.
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计算机 / AINumerical methods for differential equations
Matrix Theory and Algorithms · Differential Equations and Numerical Methods
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