ACelerated COnvex OPTimization

Project Information

ACCOPT

Grant agreement ID: 788368

DOI

10.3030/788368

Project closed

EC signature date 5 June 2018

Start date 1 September 2018

End date 31 August 2024

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 2 090 038,00

EU contribution

€ 2 090 038,00

Coordinated by

UNIVERSITE CATHOLIQUE DE LOUVAIN
Belgium

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Peer reviewed articles (25)

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

Author(s): G.N. Grapiglia, Yu. Nesterov
Published in: Optimization Methods and Software, Issue 36(1), 2021, Page(s) 145 - 170, ISSN 1055-6788
Publisher: Taylor & Francis
DOI: 10.1080/10556788.2020.1731749

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

Author(s): G. N. Grapiglia, Yu. Nesterov
Published in: SIAM Journal on Optimization, Issue 30/4, 2020, Page(s) 2750-2779, ISSN 1052-6234
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/19m1259432

Superfast second-order methods for unconstrained convex optimization

Author(s): Yurii Nesterov
Published in: Journal of Optimization Theory and Applications, Issue 191, 2021, Page(s) 1-30, ISSN 0022-3239
Publisher: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-021-01930-y

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

Author(s): Yurii Nesterov
Published in: SIAM Journal of Optimization, Issue 31(4), 2021, Page(s) 2807-2828, ISSN 1052-6234
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/20m134705x

Gradient methods with memory

Author(s): Yurii Nesterov, Mihai I. Florea
Published in: Optimization Methods and Software, Issue Online First, 2021, Page(s) 1-18, ISSN 1055-6788
Publisher: Taylor & Francis
DOI: 10.1080/10556788.2020.1858831

Contracting Proximal Methods for Smooth Convex Optimization

Author(s): Nikita Doikov, Yurii Nesterov
Published in: SIAM Journal on Optimization, Issue 30/4, 2020, Page(s) 3146-3169, ISSN 1052-6234
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/19m130769x

Affine-invariant contracting-point methods for Convex Optimization

Author(s): Nikita Doikov; Yurii Nesterov
Published in: Mathematical Programming, (2022), Issue 198(1), 2023, Page(s) 115–137, ISSN 0025-5610
Publisher: Springer Verlag
DOI: 10.1007/s10107-021-01761-9

Rates of superlinear convergence for classical quasi-Newton methods

Author(s): Anton Rodomanov, Yurii Nesterov
Published in: Mathematical Programming, Issue 188(3), 2021, Page(s) 744-769, ISSN 0025-5610
Publisher: 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

Author(s): Daniel Bankmann, Volker Mehrmann, Yurii Nesterov, Paul Van Dooren
Published in: Vietnam Journal of Mathematics, Issue 48, 2020, Page(s) 633–659, ISSN 2305-221X
Publisher: Springer Science + Business Media
DOI: 10.1007/s10013-020-00427-x

New Results on Superlinear Convergence of Classical Quasi-Newton Methods

Author(s): Anton Rodomanov, Yurii Nesterov
Published in: Journal of Optimization Theory and Applications, Issue 188/3, 2021, Page(s) 744-769, ISSN 0022-3239
Publisher: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-020-01805-8

Local convergence of tensor methods

Author(s): Nikita Doikov, Yurii Nesterov
Published in: Mathematical Programming, Issue Online First, 2021, ISSN 0025-5610
Publisher: Springer Verlag
DOI: 10.1007/s10107-020-01606-x

Inexact basic tensor methods for some classes of convex optimization problems

Author(s): Yurii Nesterov
Published in: Optimization Methods and Software, Issue Online First, 2020, Page(s) 1-29, ISSN 1055-6788
Publisher: Taylor & Francis
DOI: 10.1080/10556788.2020.1854252

Smoothness Parameter of Power of Euclidean Norm

Author(s): Anton Rodomanov, Yurii Nesterov
Published in: Journal of Optimization Theory and Applications, 2020, ISSN 0022-3239
Publisher: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-020-01653-6

Implementable tensor methods in unconstrained convex optimization

Author(s): Yurii Nesterov
Published in: Mathematical Programming, 2019, ISSN 0025-5610
Publisher: Springer Verlag
DOI: 10.1007/s10107-019-01449-1

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

Author(s): Guillaume O. Berger, P.-A. Absil, Raphaël M. Jungers, Yurii Nesterov
Published in: Journal of Optimization Theory and Applications, Issue 185(1), 2020, Page(s) 17-33, ISSN 0022-3239
Publisher: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-020-01632-x

Tensor methods for finding approximate stationary points of convex functions

Author(s): G.N. Grapiglia, Yu. Nesterov
Published in: Optimization Methods and Software, Issue Online First, 2021, ISSN 1055-6788
Publisher: Taylor & Francis
DOI: 10.1080/10556788.2020.1818082

Greedy Quasi-Newton Methods with Explicit Superlinear Convergence

Author(s): Anton Rodomanov, Yurii Nesterov
Published in: SIAM Journal on Optimization, Issue 31(1), 2021, Page(s) 785–811, ISSN 1052-6234
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/20m1320651

High-Order Optimization Methods for Fully Composite Problems

Author(s): Nikita Doikov; Yurii Nesterov
Published in: SIAM Journal on Optimization, Issue 32(3), 2022, Page(s) 2402-2427, ISSN 1052-6234
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/21m1410063

Gradient regularization of Newton method with Bregman distances

Author(s): Nikita Doikov; Yurii Nesterov
Published in: Mathematical Programming, Issue Online First, 2023, ISSN 0025-5610
Publisher: Springer Verlag
DOI: 10.1007/s10107-023-01943-7

Inexact accelerated high-order proximal-point methods

Author(s): Yurii Nesterov
Published in: Mathematical Programming, Issue 197, 2023, Page(s) 1-26, ISSN 0025-5610
Publisher: Springer Verlag
DOI: 10.1007/s10107-021-01727-x

Adaptive Third-Order Methods for Composite Convex Optimization

Author(s): G. N. Grapiglia, Yu. Nesterov
Published in: SIAM Journal on Optimization, Issue 33, 2023, Page(s) 1855-1883, ISSN 1052-6234
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/22m1480872

Minimizing Uniformly Convex Functions by Cubic Regularization of Newton Method

Author(s): Nikita Doikov, Yurii Nesterov
Published in: Journal of Optimization Theory and Applications, Issue 189, 2021, Page(s) 317-339, ISSN 0022-3239
Publisher: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-021-01838-7

Super-Universal Regularized Newton Method

Author(s): Nikita Doikov, Konstantin Mishchenko, Yurii Nesterov
Published in: SIAM Journal on Optimization, Issue 34, 2024, Page(s) 27-56, ISSN 1052-6234
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/22m1519444

Subgradient ellipsoid method for nonsmooth convex problems

Author(s): Anton Rodomanov; Yurii Nesterov
Published in: Mathematical Programming, Issue 199, 2023, Page(s) 305-341, ISSN 0025-5610
Publisher: Springer Verlag
DOI: 10.1007/s10107-022-01833-4

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

Author(s): Nesterov Yurii
Published in: Journal of Optimization Theory and Applications, Issue Online First, 2023, ISSN 0022-3239
Publisher: Kluwer Academic/Plenum Publishers
DOI: 10.1007/s10957-023-02163-x

Other (1)

Complexity and Simplicity of Optimization Problems

Author(s): Yurii Nesterov
Published in: The Project Repository Journal, Issue 6, 2020, Page(s) 130-131, ISSN 2632-4067
Publisher: European Dissemination Media

Conference proceedings (3)

Convex optimization based on global lower second-order models

Author(s): Nikita Doikov, Yurii Nesterov
Published in: Advances in Neural Information Processing Systems (NeurIPS), Issue 33, 2020, Page(s) 16546-16556
Publisher: Neural Information Processing Systems

Inexact Tensor Methods with Dynamic Accuracies

Author(s): Nikita Doikov, Yurii Nesterov
Published in: Proceedings of the 37th International Conference on Machine Learning (ICML), Issue 119, 2020, Page(s) 2577-2586
Publisher: ML Research Press

Stochastic Subspace Cubic Newton Method

Author(s): Filip Hanzely, Nikita Doikov, Peter Richtárik, Yurii Nesterov
Published in: Proceedings of the 37th International Conference on Machine Learning, Issue 119, 2020, Page(s) 4027-4038
Publisher: ML Research Press

Non-peer reviewed articles (1)

Soft clustering by convex electoral model

Author(s): Yurii Nesterov
Published in: Soft Computing, Issue 24/23, 2020, Page(s) 17609-17620, ISSN 1432-7643
Publisher: Springer Verlag
DOI: 10.1007/s00500-020-05148-4