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Variable target value relaxed alternating projection method

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Abstract

In this paper we propose a modification of the von Neumann method of alternating projection x k+1=P A P B x k where A,B are closed and convex subsets of a real Hilbert space ℋ. If Fix P A P B then any sequence generated by the classical method converges weakly to a fixed point of the operator T=P A P B . If the distance δ=inf xA,yB xy is known then one can efficiently apply a modification of the von Neumann method, which has the form x k+1=P A (x k +λ k (P A P B x k x k )) for λ k >0 depending on x k (for details see: Cegielski and Suchocka, SIAM J. Optim. 19:1093–1106, 2008). Our paper contains a generalization of this modification, where we do not suppose that we know the value δ. Instead of δ we apply its approximation which is updated in each iteration.

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References

  1. Bauschke, H.H., Borwein, J.: Dykstra’s alternating projection algorithm for two sets. J. Approx. Theory 79, 418–443 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  2. Bauschke, H.H., Borwein, J.: On projection algorithms for solving convex feasibility problems. SIAM Rev. 38, 367–426 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  3. Bauschke, H.H., Combettes, P.L., Kruk, S.G.: Extrapolation algorithm for affine-convex feasibility problems. Numer. Algorithms 41, 239–274 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  4. Bauschke, H.H., Deutsch, F., Hundal, H., Park, S.-H.: Accelerating the convergence of the method of alternating projection. Trans. AMS 355, 3433–3461 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  5. Cegielski, A.: A method of projection onto an acute cone with level control in convex minimization. Math. Program. 85, 469–490 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  6. Cegielski, A., Dylewski, R.: Selection strategies in a projection method for convex minimization problems. Discuss. Math. Differ. Incl. Control Optim. 22, 97–123 (2002)

    MATH  MathSciNet  Google Scholar 

  7. Cegielski, A., Dylewski, R.: Residual selection in a projection method for convex minimization problems. Optimization 52, 211–220 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  8. Cegielski, A., Suchocka, A.: Relaxed alternating projection methods. SIAM J. Optim. 19, 1093–1106 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  9. Combettes, P.: Inconsistent Signal Feasibility Problem: Lest Square Solutions in a Product Space. IEEE Trans. Signal Process. 42, 2955–2966 (1994)

    Article  Google Scholar 

  10. Gurin, L.G., Polyak, B.T., Raik, E.V.: The method of projection for finding the common point in convex sets. Z. Vychisl. Mat. Mat. Fiz. 7, 1211–1228 (1967) (in Russian). English translation in USSR Comput. Math. Phys. 7, 1–24 (1967)

    MATH  Google Scholar 

  11. Kim, S., Ahn, H., Cho, S.-C.: Variable target value subgradient method. Math. Program. 49, 359–369 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  12. Kiwiel, K.C.: The efficiency of subgradient projection methods for convex optimization, part I: General level methods. SIAM J. Control Optim. 34, 660–676 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  13. Opial, Z.: Weak convergence of the sequence of successive approximations for nonexpansive mappings. Bull. Am. Math. Soc. 73, 591–597 (1967)

    Article  MATH  MathSciNet  Google Scholar 

  14. Polyak, B.T.: Minimization of unsmooth functionals. Z. Vychisl. Mat. Mat. Fiz. 9, 509–521 (1969) (in Russian). English translation in USSR Comput. Math. Phys. 9, 14–29 (1969)

    Google Scholar 

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Cegielski, A., Dylewski, R. Variable target value relaxed alternating projection method. Comput Optim Appl 47, 455–476 (2010). https://doi.org/10.1007/s10589-009-9233-x

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  • DOI: https://doi.org/10.1007/s10589-009-9233-x

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