Two adaptive relaxation strategies are proposed for Anderson acceleration. They are specifically designed for applications in which mappings converge to a fixed point. Their superiority over alternative Anderson acceleration is demonstrated for linear contraction mappings. Both strategies perform well in three nonlinear fixed-point applications that include partial differential equations and the EM algorithm. One strategy surpasses all other Anderson acceleration implementations tested in terms of computation time across various specifications, including composite Anderson acceleration.

翻译：本文提出了两种自适应松弛策略用于Anderson加速算法。这些策略专门针对映射收敛至不动点的应用场景设计。在线性压缩映射中，这两种策略展现出优于其他Anderson加速算法的性能。在包含偏微分方程和EM算法的三种非线性不动点应用中，两种策略均表现良好。其中一种策略在包括复合Anderson加速在内的多种配置下，其计算时间均优于所有其他测试的Anderson加速实现方案。