Skip to main content
Log in

Discrete-time gradient flows and law of large numbers in Alexandrov spaces

  • Published:
Calculus of Variations and Partial Differential Equations Aims and scope Submit manuscript

Abstract

We develop the theory of discrete-time gradient flows for convex functions on Alexandrov spaces with arbitrary upper or lower curvature bounds. We employ different resolvent maps in the upper and lower curvature bound cases to construct such a flow, and show its convergence to a minimizer of the potential function. We also prove a stochastic version, a generalized law of large numbers for convex function valued random variables, which not only extends Sturm’s law of large numbers on nonpositively curved spaces to arbitrary lower or upper curvature bounds, but this version seems new even in the Euclidean setting. These results generalize those in nonpositively curved spaces (partly for squared distance functions) due to Bačák, Jost, Sturm and others, and the lower curvature bound case seems entirely new.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Afsari, B.: Riemannian \(L^{p}\) center of mass: existence, uniqueness, and convexity. Proc. Am. Math. Soc. 139, 655–673 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  2. Ambrosio, L., Gigli, N., Savaré, G.: Gradient Flows in Metric Spaces and in the Space of Probability Measures, 2nd edn. Birkhäuser Verlag, Basel (2008)

    MATH  Google Scholar 

  3. Arnaudon, M., Li, X.M.: Barycenters of measures transported by stochastic flows. Ann. Probab. 33, 1509–1543 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  4. Arnaudon, M., Dombry, C., Phan, A., Yang, L.: Stochastic algorithms for computing means of probability measures. Stoch. Process. Appl. 122, 1437–1455 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  5. Bačák, M.: The proximal point algorithm in metric spaces. Israel J. Math. 194, 689–701 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  6. Bačák, M.: Computing means and medians in Hadamard spaces. SIAM J. Optim. (2014), to appear. arXiv:1210.2145

  7. Bento, G.C., Cruz, J.X.: Neto, finite termination of the proximal point method for convex functions on Hadamard manifolds. Optimization (2012). doi:10.1080/02331934.2012.730050

  8. Bertsekas, D.P.: Incremental proximal methods for large scale convex optimization. Math. Program. Ser. B 129, 163–195 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  9. Bertsekas, D.P., Tsitsiklis, J.N.: Neuro-dynamic Programming. Athena Scientific, Belmont (1996)

    MATH  Google Scholar 

  10. Bhatia, R.: Positive definite matrices. In: Princeton Series in Applied Mathematics. Princeton University Press, Princeton (2007)

  11. Bhatia, R., Holbrook, J.: Riemannian geometry and matrix geometric means. Linear Algebra Appl. 413, 594–618 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  12. Brézis, H., Lions, P.-L.: Produits infinis de rèsolvantes. Israel J. Math. 29, 329–345 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  13. Burago, D., Burago, Yu., Ivanov, S.: A Course in Metric Geometry. American Mathematical Society, Providence (2001)

    Book  MATH  Google Scholar 

  14. Espínola, R., Fernández-León, A.: CAT\((k)\)-spaces, weak convergence and fixed points. J. Math. Anal. Appl. 353, 410–427 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  15. Ferreira, O.P., Oliveira, P.R.: Proximal point algorithm on Riemannian manifolds. Optimization 51, 257–270 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  16. Holbrook, J.: No dice: a deterministic approach to the Cartan centroid. J. Ramanujan Math. Soc. 27, 509–521 (2012)

    MathSciNet  MATH  Google Scholar 

  17. Jost, J.: Equilibrium maps between metric spaces. Calc. Var. Partial Differ. Equ. 2, 173–204 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  18. Jost, J.: Convex functionals and generalized harmonic maps into spaces of nonpositive curvature. Comment. Math. Helv. 70, 659–673 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  19. Jost, J.: Nonpositive Curvature: Geometric and Analytic Aspects. Birkhäuser Verlag, Basel (1997)

    Book  MATH  Google Scholar 

  20. Jost, J.: Nonlinear dirichlet forms, new directions in Dirichlet forms 1–47. In: AMS/IP Stud. Adv. Math., vol. 8. American Mathematical Society, Providence (1998)

  21. Karcher, H.: Riemannian center of mass and mollifier smoothing. Commun. Pure Appl. Math. 30, 509–541 (1977)

    Article  MathSciNet  MATH  Google Scholar 

  22. Kendall, W.S.: Probability, convexity, and harmonic maps with small image I: uniqueness and fine existence. Proc. Lond. Math. Soc. (3) 61, 371–406 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  23. Kendall, W.S.: Convexity and the hemisphere. J. Lond. Math. Soc. (2) 43, 567–576 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  24. Korf, L.A., Wets, R.J.-B.: Random lsc functions: an ergodic theorem. Math. Oper. Res. (26) 2, 421–445 (2001)

    Article  MathSciNet  Google Scholar 

  25. Kuwae, K.: Jensen’s inequality over CAT\((\kappa )\)-space with small diameter. In: Potential Theory and Stochastics in Albac. Theta Ser. Adv. Math., vol. 11, pp. 173–182. Theta, Bucharest (2009)

  26. Lawson, J., Lim, Y.: Monotonic properties of the least squares mean. Math. Ann. 351, 267–279 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  27. Li, C., López, G., Martín-Márquez, V.: Monotone vector fields and the proximal point algorithm on Hadamard manifolds. J. Lond. Math. Soc. (2) 79, 663–683 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  28. Lim, Y., Pálfia, M.: Weighted deterministic walks for the least squares mean on Hadamard spaces. Bull. Lond. Math. Soc. 46, 561–570 (2014)

  29. Lytchak, A.: Open map theorem for metric spaces. St. Petersb. Math. J. 17, 477–491 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  30. Mayer, U.F.: Gradient flows on nonpositively curved metric spaces and harmonic maps. Commun. Anal. Geom. 6, 199–253 (1998)

    MATH  Google Scholar 

  31. Moakher, M.: Means and averaging in the group of rotations. SIAM J. Matrix Anal. Appl. 24, 1–16 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  32. Nedic, A., Bertsekas, D.P.: Convergence rate of incremental subgradient algorithms. In: Stochastic Optimization: Algorithms and Applications (Gainesville, FL, 2000). Appl. Optim., vol. 54, pp. 223–264. Kluwer, Dordrecht (2001)

  33. Nedic, A., Bertsekas, D.P.: Incremental subgradient methods for nondifferentiable optimization. SIAM J. Optim. 12, 109–138 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  34. Ohta, S.: Convexities of metric spaces. Geom. Dedic. 125, 225–250 (2007)

    Article  MATH  Google Scholar 

  35. Ohta, S.: Gradient flows on Wasserstein spaces over compact Alexandrov spaces. Am. J. Math. 131, 475–516 (2009)

    Article  MATH  Google Scholar 

  36. Ohta, S.: Barycenters in Alexandrov spaces of curvature bounded below. Adv. Geom. 12, 571–587 (2012)

    MathSciNet  MATH  Google Scholar 

  37. Perel’man, G., Petrunin, A.: Quasigeodesics and gradient curves in Alexandrov spaces. Unpublished preprint. http://www.math.psu.edu/petrunin/ (1995). Accessed 12 Feb 2015

  38. Petrunin, A.: Semiconcave functions in Alexandrov’s geometry. In: Surveys in Differential Geometry, vol. XI, pp. 137–201. Int. Press, Somerville (2007)

  39. Rockafellar, R.T.: Convex Analysis. Princeton University Press, Princeton (1997)

    MATH  Google Scholar 

  40. Rockafellar, R.T., Wets, R.J.-B.: Variational Analysis. Springer, Berlin (1998)

    Book  MATH  Google Scholar 

  41. Sturm, K.-T.: Nonlinear Markov operators associated with symmetric Markov kernels and energy minimizing maps between singular spaces. Calc. Var. Partial Differ. Equ. 12, 317–357 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  42. Sturm, K.-T.: Nonlinear Markov operators, discrete heat flow, and harmonic maps between singular spaces. Potential Anal. 16, 305–340 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  43. Sturm, K.-T.: Nonlinear martingale theory for processes with values in metric spaces of nonpositive curvature. Ann. Probab. 30, 1195–1222 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  44. Sturm, K.-T.: Probability measures on metric spaces of nonpositive curvature. In: Heat Kernels and Analysis on Manifolds, Graphs, and Metric Spaces (Paris, 2002). Contemp. Math., vol. 338, pp. 357–90. Am. Math. Soc., Providence (2003)

  45. Sturm, K.-T.: A semigroup approach to harmonic maps. Potential Anal. 23, 225–277 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  46. Sturm, K.-T.: On the geometry of metric measure spaces. Acta Math. 196, 65–131 (2006)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the anonymous referee for his valuable comments, in particular improving the discussion in Sect. 6. The second author would like to thank Prof. John Holbrook for raising his attention to the approximation problem of the barycenter treated in Remark 6.8 on the sphere. The second author had doubts in the convergence of such approximation scheme in the positive curvature case, but then he learned about the favorable outcomes of Prof. Holbrook’s numerical experiments on the sphere in a private communication with him, which initiated the further study of the problem.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Miklós Pálfia.

Additional information

Communicated by J. Jost.

S. Ohta is supported by the Grant-in-Aid for Young Scientists (B) 23740048; M. Pálfia is supported by the Research Fellowship of the Canon Foundation.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ohta, Si., Pálfia, M. Discrete-time gradient flows and law of large numbers in Alexandrov spaces. Calc. Var. 54, 1591–1610 (2015). https://doi.org/10.1007/s00526-015-0837-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00526-015-0837-y

Mathematics Subject Classification

Navigation