Studying Convergence of Gradient Algorithms Via Optimal Experimental Design Theory

  • R. Haycroft
  • L. Pronzato
  • H. P. Wynn
  • A. Zhigljavsky
Part of the Springer Optimization and Its Applications book series (SOIA, volume 28)

Summary

We study the family of gradient algorithms for solving quadratic optimization problems, where the step-length γk is chosen according to a particular procedure. To carry out the study, we re-write the algorithms in a normalized form and make a connection with the theory of optimum experimental design. We provide the results of a numerical study which shows that some of the proposed algorithms are extremely efficient.

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Copyright information

© Springer Science+Business Media LLC 2009

Authors and Affiliations

  • R. Haycroft
    • 1
  • L. Pronzato
    • 2
  • H. P. Wynn
    • 3
  • A. Zhigljavsky
    • 4
  1. 1.Cardiff University, School of MathematicsCardiffUK
  2. 2. Laboratoire I3S, CNRS - UNSA, Les Algorithmes – Bˆat. Euclide B Sophia Antipolis France
  3. 3. London School of Economics and Political Science London UK
  4. 4.Cardiff University,School of MathematicsCardiffUK

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