Inexact basic tensor methods for some classes of convex optimization problems-Reference-Cited by-同舟云学术

Inexact basic tensor methods for some classes of convex optimization problems

Published:2020-12-10 Issue: Volume: Page:1-29
ISSN:1055-6788
Container-title:Optimization Methods and Software
language:en
Short-container-title:Optimization Methods and Software

Author:

Nesterov Yurii¹^ORCID

Affiliation:

1. Center for Operations Research and Econometrics (CORE), Catholic University of Louvain (UCL), Louvain-la-Neuve, Belgium

Funder

European Research Council

Publisher

Informa UK Limited

Subject

Applied Mathematics,Control and Optimization,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/10556788.2020.1854252

Reference16 articles.

1. A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications

2. Worst-case evaluation complexity for unconstrained nonlinear optimization using high-order regularized models

3. Universal Regularization Methods: Varying the Power, the Smoothness and the Accuracy

4. G. Grapiglia and Y. Nesterov, On inexact solution of auxiliary problems in tensor methods, (2019). Available at arXiv 1907.13023 [math. OC].

5. G.N. Grapiglia and Y. Nesterov, Tensor methods for minimizing functions with Hölder continuous higher-order derivatives, (2019). Available at arXiv:1904.12559 [math. OC].

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