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Complexity analysis of a sampling-based interior point method for convex optimization

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  • Badenbroek, Riley

    (Tilburg University, School of Economics and Management)

  • de Klerk, Etienne

    (Tilburg University, School of Economics and Management)

Abstract

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Suggested Citation

  • Badenbroek, Riley & de Klerk, Etienne, 2022. "Complexity analysis of a sampling-based interior point method for convex optimization," Other publications TiSEM 3d774c6d-8141-4f31-a621-5, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:3d774c6d-8141-4f31-a621-5f0d868684f2
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    File URL: https://pure.uvt.nl/ws/portalfiles/portal/46393218/Sampling_IPM_MOR_v2.1.pdf
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    References listed on IDEAS

    as
    1. Robert L. Smith, 1984. "Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed over Bounded Regions," Operations Research, INFORMS, vol. 32(6), pages 1296-1308, December.
    2. Claude J. P. Bélisle & H. Edwin Romeijn & Robert L. Smith, 1993. "Hit-and-Run Algorithms for Generating Multivariate Distributions," Mathematics of Operations Research, INFORMS, vol. 18(2), pages 255-266, May.
    3. Adam Tauman Kalai & Santosh Vempala, 2006. "Simulated Annealing for Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 31(2), pages 253-266, May.
    4. David E. Kaufman & Robert L. Smith, 1998. "Direction Choice for Accelerated Convergence in Hit-and-Run Sampling," Operations Research, INFORMS, vol. 46(1), pages 84-95, February.
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    Cited by:

    1. Riley Badenbroek & Etienne Klerk, 2022. "Simulated Annealing for Convex Optimization: Rigorous Complexity Analysis and Practical Perspectives," Journal of Optimization Theory and Applications, Springer, vol. 194(2), pages 465-491, August.

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