ACelerated COnvex OPTimization

On inexact solution of auxiliary problems in tensor methods for convex optimization

Autores: G.N. Grapiglia, Yu. Nesterov
Publicado en: Optimization Methods and Software, Edición 36(1), 2021, Página(s) 145 - 170, ISSN 1055-6788
Editor: Taylor & Francis
DOI: 10.1080/10556788.2020.1731749

Tensor Methods for Minimizing Convex Functions with Hölder Continuous Higher-Order Derivatives

Autores: G. N. Grapiglia, Yu. Nesterov
Publicado en: SIAM Journal on Optimization, Edición 30/4, 2020, Página(s) 2750-2779, ISSN 1052-6234
Editor: Society for Industrial and Applied Mathematics
DOI: 10.1137/19m1259432

Superfast second-order methods for unconstrained convex optimization

Autores: Yurii Nesterov
Publicado en: Journal of Optimization Theory and Applications, Edición 191, 2021, Página(s) 1-30, ISSN 0022-3239
Editor: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-021-01930-y

Inexact High-Order Proximal-Point Methods with Auxiliary Search Procedure

Autores: Yurii Nesterov
Publicado en: SIAM Journal of Optimization, Edición 31(4), 2021, Página(s) 2807-2828, ISSN 1052-6234
Editor: Society for Industrial and Applied Mathematics
DOI: 10.1137/20m134705x

Gradient methods with memory

Autores: Yurii Nesterov, Mihai I. Florea
Publicado en: Optimization Methods and Software, Edición Online First, 2021, Página(s) 1-18, ISSN 1055-6788
Editor: Taylor & Francis
DOI: 10.1080/10556788.2020.1858831

Contracting Proximal Methods for Smooth Convex Optimization

Autores: Nikita Doikov, Yurii Nesterov
Publicado en: SIAM Journal on Optimization, Edición 30/4, 2020, Página(s) 3146-3169, ISSN 1052-6234
Editor: Society for Industrial and Applied Mathematics
DOI: 10.1137/19m130769x

Affine-invariant contracting-point methods for Convex Optimization

Autores: Nikita Doikov; Yurii Nesterov
Publicado en: Mathematical Programming, (2022), Edición 198(1), 2023, Página(s) 115–137, ISSN 0025-5610
Editor: Springer Verlag
DOI: 10.1007/s10107-021-01761-9

Rates of superlinear convergence for classical quasi-Newton methods

Autores: Anton Rodomanov, Yurii Nesterov
Publicado en: Mathematical Programming, Edición 188(3), 2021, Página(s) 744-769, ISSN 0025-5610
Editor: Springer Verlag
DOI: 10.1007/s10107-021-01622-5

Computation of the Analytic Center of the Solution Set of the Linear Matrix Inequality Arising in Continuous- and Discrete-Time Passivity Analysis

Autores: Daniel Bankmann, Volker Mehrmann, Yurii Nesterov, Paul Van Dooren
Publicado en: Vietnam Journal of Mathematics, Edición 48, 2020, Página(s) 633–659, ISSN 2305-221X
Editor: Springer Science + Business Media
DOI: 10.1007/s10013-020-00427-x

New Results on Superlinear Convergence of Classical Quasi-Newton Methods

Autores: Anton Rodomanov, Yurii Nesterov
Publicado en: Journal of Optimization Theory and Applications, Edición 188/3, 2021, Página(s) 744-769, ISSN 0022-3239
Editor: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-020-01805-8

Local convergence of tensor methods

Autores: Nikita Doikov, Yurii Nesterov
Publicado en: Mathematical Programming, Edición Online First, 2021, ISSN 0025-5610
Editor: Springer Verlag
DOI: 10.1007/s10107-020-01606-x

Inexact basic tensor methods for some classes of convex optimization problems

Autores: Yurii Nesterov
Publicado en: Optimization Methods and Software, Edición Online First, 2020, Página(s) 1-29, ISSN 1055-6788
Editor: Taylor & Francis
DOI: 10.1080/10556788.2020.1854252

Smoothness Parameter of Power of Euclidean Norm

Autores: Anton Rodomanov, Yurii Nesterov
Publicado en: Journal of Optimization Theory and Applications, 2020, ISSN 0022-3239
Editor: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-020-01653-6

Implementable tensor methods in unconstrained convex optimization

Autores: Yurii Nesterov
Publicado en: Mathematical Programming, 2019, ISSN 0025-5610
Editor: Springer Verlag
DOI: 10.1007/s10107-019-01449-1

On the Quality of First-Order Approximation of Functions with Hölder Continuous Gradient

Autores: Guillaume O. Berger, P.-A. Absil, Raphaël M. Jungers, Yurii Nesterov
Publicado en: Journal of Optimization Theory and Applications, Edición 185(1), 2020, Página(s) 17-33, ISSN 0022-3239
Editor: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-020-01632-x

Tensor methods for finding approximate stationary points of convex functions

Autores: G.N. Grapiglia, Yu. Nesterov
Publicado en: Optimization Methods and Software, Edición Online First, 2021, ISSN 1055-6788
Editor: Taylor & Francis
DOI: 10.1080/10556788.2020.1818082

Greedy Quasi-Newton Methods with Explicit Superlinear Convergence

Autores: Anton Rodomanov, Yurii Nesterov
Publicado en: SIAM Journal on Optimization, Edición 31(1), 2021, Página(s) 785–811, ISSN 1052-6234
Editor: Society for Industrial and Applied Mathematics
DOI: 10.1137/20m1320651

High-Order Optimization Methods for Fully Composite Problems

Autores: Nikita Doikov; Yurii Nesterov
Publicado en: SIAM Journal on Optimization, Edición 32(3), 2022, Página(s) 2402-2427, ISSN 1052-6234
Editor: Society for Industrial and Applied Mathematics
DOI: 10.1137/21m1410063

Gradient regularization of Newton method with Bregman distances

Autores: Nikita Doikov; Yurii Nesterov
Publicado en: Mathematical Programming, Edición Online First, 2023, ISSN 0025-5610
Editor: Springer Verlag
DOI: 10.1007/s10107-023-01943-7

Inexact accelerated high-order proximal-point methods

Autores: Yurii Nesterov
Publicado en: Mathematical Programming, Edición 197, 2023, Página(s) 1-26, ISSN 0025-5610
Editor: Springer Verlag
DOI: 10.1007/s10107-021-01727-x

Minimizing Uniformly Convex Functions by Cubic Regularization of Newton Method

Autores: Nikita Doikov, Yurii Nesterov
Publicado en: Journal of Optimization Theory and Applications, Edición 189, 2021, Página(s) 317-339, ISSN 0022-3239
Editor: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-021-01838-7

Subgradient ellipsoid method for nonsmooth convex problems

Autores: Anton Rodomanov; Yurii Nesterov
Publicado en: Mathematical Programming, Edición 199, 2023, Página(s) 305-341, ISSN 0025-5610
Editor: Springer Verlag
DOI: 10.1007/s10107-022-01833-4

Set-Limited Functions and Polynomial-Time Interior-Point Methods

Autores: Nesterov Yurii
Publicado en: Journal of Optimization Theory and Applications, Edición Online First, 2023, ISSN 0022-3239
Editor: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-023-02163-x

Complexity and Simplicity of Optimization Problems

Autores: Yurii Nesterov
Publicado en: The Project Repository Journal, Edición 6, 2020, Página(s) 130-131, ISSN 2632-4067
Editor: European Dissemination Media

Convex optimization based on global lower second-order models

Autores: Nikita Doikov, Yurii Nesterov
Publicado en: Advances in Neural Information Processing Systems (NeurIPS), Edición 33, 2020, Página(s) 16546-16556
Editor: Neural Information Processing Systems

Inexact Tensor Methods with Dynamic Accuracies

Autores: Nikita Doikov, Yurii Nesterov
Publicado en: Proceedings of the 37th International Conference on Machine Learning (ICML), Edición 119, 2020, Página(s) 2577-2586
Editor: ML Research Press

Stochastic Subspace Cubic Newton Method

Autores: Filip Hanzely, Nikita Doikov, Peter Richtárik, Yurii Nesterov
Publicado en: Proceedings of the 37th International Conference on Machine Learning, Edición 119, 2020, Página(s) 4027-4038
Editor: ML Research Press

Soft clustering by convex electoral model

Autores: Yurii Nesterov
Publicado en: Soft Computing, Edición 24/23, 2020, Página(s) 17609-17620, ISSN 1432-7643
Editor: Springer Verlag
DOI: 10.1007/s00500-020-05148-4

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