TENSOR METHODS FOR MINIMIZING CONVEX FUNCTIONS WITH HOLDER CONTINUOUS HIGHER-ORDER DERIVATIVES

被引:11
作者
Grapiglia, G. N. [1 ]
Nesterov, Yu. [2 ]
机构
[1] Univ Fed Parana, Dept Matemat, Ctr Politecn, BR-81531980 Curitiba, Parana, Brazil
[2] Catholic Univ Louvain UCL, Ctr Operat Res & Econometr CORE, B-1348 Louvain La Neuve, Belgium
基金
欧洲研究理事会;
关键词
unconstrained minimization; high-order methods; tensor methods; Holder condition; worst-case global complexity bounds; REGULARIZED NEWTON METHODS; CUBIC REGULARIZATION; OPTIMIZATION; COMPLEXITY;
D O I
10.1137/19M1259432
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, we study p-order methods for unconstrained minimization of convex functions that are p-times differentiable (p >= 2) with nu-Holder continuous pth derivatives. We propose tensor schemes with and without acceleration. For the schemes without acceleration, we establish iteration complexity bounds of O (epsilon(-1/(p+nu-1))) for reducing the functional residual below a given epsilon is an element of (0, 1). Assuming that nu is known, we obtain an improved complexity bound of O (epsilon(-1/(P+nu))) for the corresponding accelerated scheme. For the case in which nu is unknown, we present a universal accelerated tensor scheme with iteration complexity of O (epsilon(-P/[(P+1)(P+nu-1)])). A lower complexity bound of O (epsilon(-2/[3(P+nu)-2])) is also obtained for this problem class.
引用
收藏
页码:2750 / 2779
页数:30
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