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On the Convergence of a Greedy Rank-One Update Algorithm for a Class of Linear Systems

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Abstract

In this paper we study the convergence of the well-known Greedy Rank-One Update Algorithm. It is used to construct the rank-one series solution for full-rank linear systems. The existence of the rank one approximations is also not new, but surprisingly the focus there has been more on the applications side more that in the convergence analysis. Our main contribution is to prove the convergence of the algorithm and also we study the required rank one approximation in each step. We also give some numerical examples and describe its relationship with the Finite Element Method for High-Dimensional Partial Differential Equations based on the tensorial product of one-dimensional bases. We illustrate this situation taking as a model problem the multidimensional Poisson equation with homogeneous Dirichlet boundary condition.

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References

  1. Ammar A, Mokdad B, Chinesta F, Keunings R (2006) A new family of solvers for some classes of multidimensional partial differential equations encountered in Kinetic Theory modelling Complex Fluids. J Non-Newton Fluid Mech 139:153–176

    Article  MATH  Google Scholar 

  2. Ammar A, Mokdad B, Chinesta F, Keunings R (2007) A new family of solvers for some classes of multidimensional partial differential equations encountered in Kinetic Theory modelling Complex Fluids. Part II: Transient simulations using space-time separated representations. J Non-Newton Fluid Mech 144:98–121

    Article  MATH  Google Scholar 

  3. Beylkin G, Mohlenkamp MJ (2005) Algorithms for numerical analysis in high dimensions. SIAM J Sci Comput 26(6):2133–2159

    Article  MATH  MathSciNet  Google Scholar 

  4. de Silva V, Lim L-H (2008) Tensor Rank and Ill-posedness of the best low-rank approximation problem. SIAM J Matrix Anal Appl 30(3):1084–1127

    Article  MathSciNet  Google Scholar 

  5. Graham A (1981) Kronecker products and matrix calculus with applications. Wiley, New York

    MATH  Google Scholar 

  6. Grasdyck L (2004) Existence and computation of low Kronecker-rank approximations for large linear systems of tensor product structure. Computing 72:247–265

    MathSciNet  Google Scholar 

  7. Friedman JH, Stuezle W (1981) Projection pursuit regression. J Am Statist Assoc 76:817–823

    Article  Google Scholar 

  8. Huber PJ (1985) Projection pursuit. Ann Statist 13(2):435–475

    Article  MATH  MathSciNet  Google Scholar 

  9. Kolda T (2001) Orthogonal tensor decompositions. SIAM J Matrix Anal Appl 20(1):243–255

    Article  MathSciNet  Google Scholar 

  10. de Lathauwer L, de Moor B, Vandewalle J (2000) A multilinear singular value decomposition. SIAM J Matrix Anal Appl 21(4):1253–1278

    Article  MATH  MathSciNet  Google Scholar 

  11. de Lathauwer L, de Moor B, Vandewalle J (2000) On the best rank-1 and rank-(R 1,…,R N ) approximations of high order tensors. SIAM J Matrix Anal Appl 21(4):1324–1342

    Article  MATH  MathSciNet  Google Scholar 

  12. Mallat S, Zhang Z (1993) Matching pursuit with time-frequency dictionaries. IEEE Trans Signal Process 41:3397–3415

    Article  MATH  Google Scholar 

  13. Ruszczyński A (2006) Nonlinear optimization. Princeton University Press, Princeton

    MATH  Google Scholar 

  14. N Temlyakov V (2008) Greedy approximation. Acta Numer, pp 235–409

  15. Van Loan CF (2000) The ubiquitous Kronecker product. J Comput Appl Math 123:85–100

    Article  MATH  MathSciNet  Google Scholar 

  16. Zhang T, Golub G (2000) Rank-one approximation to high order tensors. SIAM J Matrix Anal Appl 21(4):1253–1278

    Article  MathSciNet  Google Scholar 

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Correspondence to A. Ammar.

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This work has been partially supported by the SEJ2006-05051 grant of the Ministerio de Educación y Ciencia and PRCEU-UCH07/08 grant of the Universidad CEU Cardenal Herrera.

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Ammar, A., Chinesta, F. & Falcó, A. On the Convergence of a Greedy Rank-One Update Algorithm for a Class of Linear Systems. Arch Computat Methods Eng 17, 473–486 (2010). https://doi.org/10.1007/s11831-010-9048-z

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  • DOI: https://doi.org/10.1007/s11831-010-9048-z

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