Rounding of convex sets and efficient gradient methods for linear programming problems
AbstractIn 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
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Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2004004.
Date of creation: 00 Feb 2004
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nonlinear optimization; convex optimization; complexity bounds; relative accuracy; fully polynomial approximation schemes; gradient methods; optimal methods;
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- NESTEROV, Yu, 2003. "Unconstrained convex minimization in relative scale," CORE Discussion Papers 2003096, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- 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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