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Rounding of convex sets and efficient gradient methods for linear programming problems

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  • NESTEROV, Yu

Abstract

In this paper we propose new efficient gradient schemes for two non-trivial classes of linear programming problems. These schemes are designed to compute approximate solutions withrelative accuracy . We prove that the upper complexity bound for both ln schemes is O( n m ln n) iterations of a gradient-type method, where n and m, (n

Suggested Citation

  • NESTEROV, Yu, 2004. "Rounding of convex sets and efficient gradient methods for linear programming problems," CORE Discussion Papers 2004004, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2004004
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    File URL: https://uclouvain.be/en/research-institutes/immaq/core/dp-2004.html
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    1. NESTEROV, Yu, 2003. "Unconstrained convex minimization in relative scale," CORE Discussion Papers 2003096, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    Cited by:

    1. Wei-jie Cong & Hong-wei Liu & Feng Ye & Shui-sheng Zhou, 2012. "Rank-two update algorithms for the minimum volume enclosing ellipsoid problem," Computational Optimization and Applications, Springer, vol. 51(1), pages 241-257, January.

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