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A family of Barzilai-Borwein steplengths from the viewpoint of scaled total least squares

  • Shiru Li,
  • Tao Zhang,
  • Yong Xia

摘要

The Barzilai-Borwein (BB) steplengths play great roles in practical gradient methods for solving unconstrained optimization problems. Motivated by the observation that the two well-known BB steplengths correspond to the ordinary and the data least squares, respectively, we introduce a novel family of BB steplengths from the viewpoint of scaled total least squares. Numerical experiments demonstrate that high performance can be received by a carefully-selected BB steplength in the new family.