Superlinear Convergence and Implicit Filtering

نویسندگان

  • T. D. Choi
  • C. T. Kelley
چکیده

In this note we show how the implicit filtering algorithm can be coupled with the BFGS quasi-Newton update to obtain a superlinearly convergent iteration if the noise in the objective function decays sufficiently rapidly as the optimal point is approached. We show how known theory for the noise-free case can be extended and thereby provide a partial explanation for the good performance of quasi-Newton methods when coupled with implicit filtering.

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عنوان ژورنال:
  • SIAM Journal on Optimization

دوره 10  شماره 

صفحات  -

تاریخ انتشار 2000