Geodesic
Algorithms for approximate calculation of the minimum of a convex function from its values
Matematičeskie zametki, Tome 59 (1996) no. 1, pp. 95-102 Cet article a éte moissonné depuis la source Math-Net.Ru

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The paper deals with a numerical minimization problem for a convex function defined on a convex $n$-dimensional domain and continuous (but not necessarily smooth). The values of the function can be calculated at any given point. It is required to find the minimum with desired accuracy. A new algorithm for solving this problem is presented, whose computational complexity as $n\to\infty$ is considerably less than that of similar algorithms known to the author. In fact, the complexity is improved from $Cn^7\ln^2(n+1)$ [4] to $Cn^2\ln(n+1)$. 
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     title = {Algorithms for approximate calculation of the minimum of a~convex function from its values},
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V. Yu. Protasov. Algorithms for approximate calculation of the minimum of a convex function from its values. Matematičeskie zametki, Tome 59 (1996) no. 1, pp. 95-102. http://geodesic.mathdoc.fr/item/MZM_1996_59_1_a8/

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[2] Levin A. Yu., “Ob odnom algoritme minimizatsii vypuklykh funktsii”, Dokl. AN SSSR, 160:6 (1965), 1241–1243

[3] Yudin D. B., Goryashko D. M., Nemirovskii A. S., Matematicheskie metody optimizatsii ustroistv i algoritmov na ASU, Radio i svyaz, M., 1982 | Zbl

[4] Gusman M., Differentsirovanie integralov v $\mathbb R^n$, Mir, M., 1978

[5] Mityagin B. S., “Dva neravenstva dlya ob'emov vypuklykh tel”, Matem. zametki, 5:5 (1959), 20–26