Skip to main content

Souriau Exponential Map Algorithm for Machine Learning on Matrix Lie Groups

  • Conference paper
  • First Online:
Geometric Science of Information (GSI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11712))

Included in the following conference series:

Abstract

Jean-Marie Souriau extended Urbain Jean Joseph Leverrier algorithm to compute characteristic polynomial of a matrix in 1948. This Souriau algorithm could be used to compute exponential map of a matrix that is a challenge in Lie Group Machine Learning. Main property of Souriau Exponential Map numerical scheme is its scalability with highly parallelization.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Souriau, J.-M.: Une méthode pour la décomposition spectrale et l’inversion des matrices. CRAS 227(2), 1010–1011 (1948)

    MATH  Google Scholar 

  2. Souriau, J.-M.: Calcul Linéaire. EUCLIDE, Introduction aux études Scientifiques, vol. 1. Presses Universitaires de France, Paris (1959)

    Google Scholar 

  3. Souriau, J.-M.; Vallée, C.; Réaud, K.; Fortuné, D.: Méthode de Le Verrier–Souriau et équations différentielles linéaires. CRAS s. IIB Mech. 328(10), 773–778 (2000)

    Google Scholar 

  4. Souriau, J.-M.: Grammaire de la Nature. Private publication (2007)

    Google Scholar 

  5. Thomas, F.: Nouvelle méthode de résolution des équations du mouvement de systèmes vibratoires linéaire, discrets, DEA Mécanique, université de Poitiers (1998)

    Google Scholar 

  6. Réaud, K., Fortuné, D., Prudhorffne, S. Vallée, C.: Méthode d’étude des vibrations d’un système mécanique non basée sur le calcul de ses modes propres. XVème Congrès français de Mécanique, Nancy, (2001)

    Google Scholar 

  7. Champion-Réaud, K.: Méthode d’étude des vibrations d’un système mécanique non basée sur le calcul de ses modes propres. SupAéro PhD (2002)

    Google Scholar 

  8. Réaud, K., Vallée, Cl., Fortuné, D.: Détermination des vecteurs propres d’un système vibratoire par exploitation du concept de matrice adjuguée. 6ème Colloque national en calcul des structures, Giens (2003)

    Google Scholar 

  9. Champion-Réaud, K.; Vallée, C.; Fortuné, D. Champion-Réaud, J.L.: Extraction des pulsations et formes propres de la réponse d’un système vibratoire. 16ème Congrès Français de Mécanique, Nice, (2003)

    Google Scholar 

  10. Vallée, C., Fortuné, D., Champion-Réaud, K.: A general solution of a linear dissipative oscillatory system avoiding decomposition into eigenvectors. J. Appl. Math. Mech. 69, 837–843 (2005)

    Article  MathSciNet  Google Scholar 

  11. Le Verrier, U.: Sur les variations séculaires des éléments des orbites pour les sept planètes principales. J. de Math. (1) 5, 230 (1840)

    Google Scholar 

  12. Le Verrier, U.: Variations séculaires des éléments elliptiques des sept planètes principales. I Math. Pures Appli. 4, 220–254 (1840)

    Google Scholar 

  13. Juhel, A.: Le Verrier et la première détermination des valeurs propres d’une matrice, Bibnum, Physique (2011)

    Google Scholar 

  14. Tong, M.D., Chen, W.K.: A novel proof of the Souriau-Frame-Faddeev algorithm. IEEE Trans. Autom. Control 38, 1447–1448 (1993)

    Article  MathSciNet  Google Scholar 

  15. Faddeev, D. K.; Sominsky, I. S.: Problems in Higher Algebra, Problem 979. Mir Publishers, Moskow-Leningrad (1949)

    Google Scholar 

  16. Frame, J.S.: A simple recursion formula for inverting a matrix. Bull. Amer. Math. Soc. 56, 1045 (1949)

    Google Scholar 

  17. Forsythe, G.E., Straus, L.W.: The Souriau-Frame characteristic equation algorithm on a digital computer. J. Math. Phys. Stud. Appl. Math. 34(1–4), 152–156 (1955)

    MathSciNet  MATH  Google Scholar 

  18. Fadeev, D.K. Fadeeva, V.N.: Computational Methods of Linear Algebra (translated from Russian by R. C. Williams). W. H. Freeman and Co., San Francisco (1963)

    Google Scholar 

  19. Greville, T.N.E.: The Souriau-Frame algorithm and the Drazin pseudoinverse. Linear Algebr. Its Appl. 6, 205 (1973)

    Article  MathSciNet  Google Scholar 

  20. Downs, T.: Some properties of the Souriau-frame algorithm with application to the inversion of rational matrices. SIAM J. on Applied Mathematics 28(2), 237–251 (1975)

    Article  MathSciNet  Google Scholar 

  21. Csanky, L.: Almost parallel matrix inversion algorithms. SIAM 618–623 (1976)

    Google Scholar 

  22. Hartwig, R.E.: More on the Souriau-Frame algorithm and the Drazin inverse. SIAM J. Appl. Math. 31(1), 42–46 (1976)

    Article  MathSciNet  Google Scholar 

  23. Hou, S.-H.: A simple proof of the Leverrier-Faddeev characteristic polynomial algorithm. SIAM Rev. 40(3), 706–709 (1998)

    Article  MathSciNet  Google Scholar 

  24. Helmberg, G., Wagner, P., Veltkamp, G.: On Faddeev-Leverrier’s method fort the computation of the characteristic polynomial of a matrix and of eigenvectors. Linear Algebra Its Appl. 185, 219–233 (1993)

    Article  MathSciNet  Google Scholar 

  25. Barnett, S.: Leverrier’s algorithm: a new proof and extensions. SIAM J. Matrix Anal. Appl. 10, 551–556 (1989)

    Article  MathSciNet  Google Scholar 

  26. Keller-Gehrig, W.: Fast algorithms for the characteristic polynomial. Theor. Comput. Sci. 36, 309–317 (1985)

    Article  MathSciNet  Google Scholar 

  27. Preparata, F., Et Sarwate, D.: An improved parallel processor bound in fast matrix inversion. Inf. Process. Lett. 7(3), 148–150 (1978)

    Article  MathSciNet  Google Scholar 

  28. Pernet, C.: Algèbre linéaire exacte efficace: le calcul du polynôme caractéristique, PhD Université Joseph Fourier, 27 (2006)

    Google Scholar 

  29. Eriksen, P.S.: Geodesics connected with the fisher metric on the multivariate normal manifold. Technical report, 86-13; Inst. of Elec. Sys., Aalborg University (1986)

    Google Scholar 

  30. Eriksen, P.S.: Geodesics connected with the Fisher metric on the multivariate normal manifold. In Proceedings of the GST Workshop, Lancaster, UK, 28–31 October 1987

    Google Scholar 

  31. Moler, C.B., van Loan, C.F.: Nineteen dubious ways to compute the exponential of a matrix. SIAM Rev. 20, 801–836 (2003)

    Article  MathSciNet  Google Scholar 

  32. Hochbruck, M., Lubich, C., Selhofer, H.: Exponential integrators for large systems of differential equations. SIAM J. Sci. Comput. 19(5), 1552–1574 (1998)

    Article  MathSciNet  Google Scholar 

  33. Iserles, A., Zanna, A.: Efficient computation of the matrix exponential by generalized polar decompositions. SIAM J. Numer. Anal. 42(5), 2218–2256 (2005)

    Article  MathSciNet  Google Scholar 

  34. Celledoni, E., Iserles, A.: Approximating the exponential from a Lie algebra to a Lie group. Math. Comput. 69, 1457–1480 (2000)

    Article  MathSciNet  Google Scholar 

  35. Celledoni, E., Iserles, A.: Methods for the approximation of the matrix exponential in a Lie-algebraic setting. IMA J. Numer. Anal. 21, 463–488 (2001)

    Article  MathSciNet  Google Scholar 

  36. Leite, F.S., Crouch, P.: Closed forms for the exponential mapping on matrix Lie groups based on Putzer’s method. J. Math. Phys. 40(7), 3561–3568 (1999)

    Article  MathSciNet  Google Scholar 

  37. Lewis, D., Olver, P.J.: Geometric integration algorithms on homogeneous manifolds’. Found. Comput. Math. 2, 363–392 (2002)

    Article  MathSciNet  Google Scholar 

  38. Munthe-Kaas, H., Quispel, R.G.W., Zanna, A.: Generalized polar decompositions on Lie groups with involutive automorphisms. Found. Comput. Math. 1(3), 297–324 (2001)

    Article  MathSciNet  Google Scholar 

  39. Saad, Y.: Analysis of some Krylov subspace approximations to the matrix exponential operator. SIAM J. Numer. Anal. 29, 209–228 (1992)

    Article  MathSciNet  Google Scholar 

  40. Zanna, A.: Recurrence relation for the factors in the polar decomposition on Lie groups. Technical report, Report no. 192, Dep. of Infor., Univ. of Bergen, Math. Comp. (2000)

    Google Scholar 

  41. Zanna, A., Munthe-Kaas, H.Z.: Generalized polar decompositions for the approximation of the matrix exponential’. SIAM J. Matrix Anal. 23(3), 840–862 (2002)

    Article  MathSciNet  Google Scholar 

  42. Nobari, E., Hosseini, S.M.: A method for approximation of the exponential map in semidirect product of matrix Lie groups and some applications. J. Comput. Appl. Math. 234(1), 305–315 (2010)

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgement

I would like to show my gratitude Ms. Danielle Fortuné from University of Poitiers, for giving me some documents from Claude Vallée and Jean-Marie Souriau archives.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Frédéric Barbaresco .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Barbaresco, F. (2019). Souriau Exponential Map Algorithm for Machine Learning on Matrix Lie Groups. In: Nielsen, F., Barbaresco, F. (eds) Geometric Science of Information. GSI 2019. Lecture Notes in Computer Science(), vol 11712. Springer, Cham. https://doi.org/10.1007/978-3-030-26980-7_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-26980-7_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26979-1

  • Online ISBN: 978-3-030-26980-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics