The UCF Mathematics and Applications Seminar, which takes place every Friday from 10:30am to 11:30am in MSB 318, provides a venue for researchers to present their current work, foster new collaborations, and showcase both foundational mathematics and its applications to graduate and undergraduate students.

Dr. Teng Zhang will be speaking at this seminar about improved convergence rates of Anderson acceleration for a large class of fixed-point iterations.

Abstract: This talk studies Anderson acceleration (AA) for fixed-point methods. It provides the first proof that when the operator q is linear and symmetric, AA improves the root-linear convergence factor over the fixed-point iterations. When q is nonlinear, yet has a symmetric Jacobian at the solution, a slightly modified AA algorithm is proved to have an analogous root-linear convergence factor improvement over fixed-point iterations. Simulations verify our observations. Furthermore, experiments with different data models demonstrate AA is significantly superior to the standard fixed-point methods for Tyler's M-estimation.

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