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A Riemannian Dennis-Moré Condition

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High-Performance Scientific Computing

Abstract

In this paper, we generalize from Euclidean spaces to Riemannian manifolds an important result in optimization that guarantees Riemannian quasi-Newton algorithms converge superlinearly.

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References

  1. Absil, P.A., Baker, C.G., Gallivan, K.A.: Trust-region methods on Riemannian manifolds. Found. Comput. Math. 7(3), 303–330 (2007) doi:10.1007/s10208-005-0179-9

    Article  MathSciNet  MATH  Google Scholar 

  2. Absil, P.-A., Mahony, R., Sepulchre, R.: Optimization Algorithms on Matrix Manifolds. Princeton University Press, New Jersey (2008)

    MATH  Google Scholar 

  3. Adler, R.L., Dedieu, J.P., Margulies, J.Y., Martens, M., Shub, M.: Newton’s method on Riemannian manifolds and a geometric model for the human spine. IMA J. Numer. Anal. 22(3), 359–390 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  4. Baker, C.G.: Riemannian manifold trust-region methods with applications to eigenproblems. Ph.D. thesis, School of Computational Science, Florida State University (2008)

    Google Scholar 

  5. Dennis, J.E., Schnabel, R.B.: Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Springer, New Jersey (1983)

    MATH  Google Scholar 

  6. Dreisigmeyer, D.W.: Direct search algorithms over Riemannian manifolds (2006). Optimization Online 2007-08-1742

    Google Scholar 

  7. Edelman, A., Arias, T.A., Smith, S.T.: The geometry of algorithms with orthogonality constrains. SIAM J. Matrix Anal. Appl. 20(2), 303–353 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  8. Gabay, D.: Minimizing a differentiable function over a differential manifold. J. Optim. Theory Appl. 37(2), 177–219 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  9. Helmke, U., Moore, J.: Optimization and Dynamical Systems. Springer, Berlin (1994)

    Google Scholar 

  10. Qi, C.: Numerical optimization on Riemannian manifolds. Ph.D. thesis, Florida State University, Tallahassee, FL, USA (2011)

    Google Scholar 

  11. Smith, S.T.: Optimization techniques on Riemannian manifolds. In: Bloch, A. (ed.) Hamiltonian and Gradient Flows, Algorithms and Control. Fields Inst. Commun., vol. 3, pp. 113–136. Amer. Math. Soc., Providence (1994)

    Google Scholar 

  12. Yang, Y.: Globally convergent optimization algorithms on Riemannian manifolds: Uniform framework for unconstrained and constrained optimization. J. Optim. Theory Appl. 132(2), 245–265 (2007). doi:10.1007/s10957-006-9081-0

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

This paper presents research results of the Belgian Network DYSCO (Dynamical Systems, Control, and Optimization), funded by the Interuniversity Attraction Poles Programme, initiated by the Belgian State, Science Policy Office. The scientific responsibility rests with its authors.

This work was performed in part while the first author was a Visiting Professor at the Institut de mathématiques pures et appliquées (MAPA) at Université catholique de Louvain.

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Correspondence to Kyle A. Gallivan .

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© 2012 Springer-Verlag London Limited

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Gallivan, K.A., Qi, C., Absil, PA. (2012). A Riemannian Dennis-Moré Condition. In: Berry, M., et al. High-Performance Scientific Computing. Springer, London. https://doi.org/10.1007/978-1-4471-2437-5_14

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  • DOI: https://doi.org/10.1007/978-1-4471-2437-5_14

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2436-8

  • Online ISBN: 978-1-4471-2437-5

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