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- W2013233766 abstract "The purpose of this paper is to provide improved complexity results for several classes of structured convex optimization problems using the theory of self-concordant functions developed by Nesterov and Nemirovski in SIAM Studies in Applied Mathematics, SIAM Publications, Philadelphia, 1994. We describe the classical short-step interior-point method and optimize its parameters in order to provide the best possible iteration bound. We also discuss the necessity of introducing two parameters in the definition of self-concordancy and which one is the best to fix. A lemma due to den Hertog et al. in Mathematical Programming Series B 69 (1) (1995) is improved, which allows us to review several classes of structured convex optimization problems and improve the corresponding complexity results." @default.
- W2013233766 created "2016-06-24" @default.
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- W2013233766 date "2002-12-01" @default.
- W2013233766 modified "2023-09-27" @default.
- W2013233766 title "Improving complexity of structured convex optimization problems using self-concordant barriers" @default.
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- W2013233766 doi "https://doi.org/10.1016/s0377-2217(02)00297-7" @default.
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