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A test for cancellation errors in quasi-Newton methods

Published: 01 June 1992 Publication History

Abstract

It has recently been shown that cancellation errors in a quasi-Newton method can increase without bound as the method converges. A simple test is presented to determine when cancellation errors could lead to significant contamination of the approximating matrix.

References

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AL-BAALI, M., AND FLETCHER, R. Variational methods for nonhnear least squares. J. Oper. Res. Soc. 36 (1985), 405 421.
[2]
BYRD, R. H., NOCEDAL, J, AND YUAN, Y. Global convergence of a class of quasi-Newton methods on convex problems. SIAM J. Numer. Anal. 24 (1987), 1171 1190.
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FLETCHER, R. Function minimization without evaluating derivatives--A review. Coraput. J 8 (1965), 33-41.
[4]
FLETCHER, R. Practical Methods of Optimization, Volume 1, Unconstrained Optimization. Wiley, Chichester, 1980
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FLETCHER, R Cancellation errors in quasi-Newton methods SIAM J Sci. Stat Comput. 7 (1986), 1387-1399.
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FLETCHER, R., AND POWELL, M J. D A rapidly convergent descent method for minimization. Comput. J. 6 (1963), 163-168.
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POWELL, M. J D. How bad are the BFGS and DFP methods when the objective function is quadratic? Math. Program. 34 (1986), 34-47.
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PRESS, W. H., FLANNERY, B P., TEUKOLSKY, S. A., ANn VETTERLING, W T Numerical Recipes: The Art of Sczentific Computing. Cambridge Univ. Press, Cambridge, Mass, 1987, 007 312.
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SCHNABEL, R. B., KOONTZ, J. E., AND WEISS, B. E. A modular system of algorithms for unconstrained minimization. ACM Trans. Math Softw 11 (1985), 419-440.
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Cited By

View all
  • (2008)Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimizationComputational Optimization and Applications10.1007/s10589-007-9050-z39:1(1-16)Online publication date: 1-Jan-2008

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Florin Popentiu

Gurwitz describes a heuristic test for estimating the effect of the cancellation error on the approximating matrix in quasi-Newton methods. After a review of the theoretical results (which are largely due to R. Fletcher), the author suggests a test for stopping the update of the approximating matrix. This test can replace Fletcher's more complicated test based on the computation of the upper bound for the effect of cancellation errors and the scalar measure of the size of the correction. Tables I and II contain numerical trials on the Rosenbrock, Chebyquad, and trigonometric functions, which prove the correctness of the test. The proposed test can easily be encoded and saves computer resources. The text is concise, the references are good, and the terminology is suitable.

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Published In

cover image ACM Transactions on Mathematical Software
ACM Transactions on Mathematical Software  Volume 18, Issue 2
June 1992
124 pages
ISSN:0098-3500
EISSN:1557-7295
DOI:10.1145/146847
Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 1992
Published in TOMS Volume 18, Issue 2

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Author Tags

  1. cancellation error
  2. quasi-Newton update
  3. unconstrained optimization

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Cited By

View all
  • (2008)Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimizationComputational Optimization and Applications10.1007/s10589-007-9050-z39:1(1-16)Online publication date: 1-Jan-2008

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