Adaptive Mirror Descent Algorithms for Convex and Strongly Convex Optimization Problems with Functional Constraints

Mirror Descent ◽

Adaptive Mirror ◽

Adaptive mirror descent algorithms for convex and strongly convex optimization problems with functional constraints

Diskretnyi analiz i issledovanie operatsii ◽

10.33048/daio.2019.26.636 ◽

2018 ◽

Vol 26 (3) ◽

pp. 88-114

Author(s):

F. S. Stonyakin ◽

M. Alkousa ◽

A. N. Stepanov ◽

A. A. Titov

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Functional Constraints ◽

Descent Algorithms ◽

Strongly Convex ◽

Mirror Descent ◽

Adaptive Mirror ◽

On the transient growth of Nesterov’s accelerated method for strongly convex optimization problems

2020 59th IEEE Conference on Decision and Control (CDC) ◽

10.1109/cdc42340.2020.9304412 ◽

2020 ◽

Author(s):

Samantha Samuelson ◽

Hesameddin Mohammadi ◽

Mihailo R. Jovanovic

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Transient Growth ◽

Strongly Convex ◽

Performance of noisy Nesterov's accelerated method for strongly convex optimization problems

2019 American Control Conference (ACC) ◽

10.23919/acc.2019.8814680 ◽

2019 ◽

Cited By ~ 3

Author(s):

Hesameddin Mohammadi ◽

Meisam Razaviyayn ◽

Mihailo R. Jovanovic

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Strongly Convex ◽

New results on subgradient methods for strongly convex optimization problems with a unified analysis

Computational Optimization and Applications ◽

10.1007/s10589-016-9841-1 ◽

2016 ◽

Vol 65 (1) ◽

pp. 127-172 ◽

Cited By ~ 1

Author(s):

Masaru Ito

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Subgradient Methods ◽

Strongly Convex ◽

A BFGS-IP algorithm for solving strongly convex optimization problems with feasibility enforced by an exact penalty approach

Mathematical Programming ◽

10.1007/s101070100283 ◽

2002 ◽

Vol 92 (3) ◽

pp. 393-424

Author(s):

J. Charles Gilbert ◽

Paul Armand ◽

Sophie Jan-J�gou

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Exact Penalty ◽

Strongly Convex ◽

Penalty Approach ◽

Accelerated Randomized Mirror Descent Algorithms for Composite Non-strongly Convex Optimization

Journal of Optimization Theory and Applications ◽

10.1007/s10957-018-01469-5 ◽

2019 ◽

Vol 181 (2) ◽

pp. 541-566 ◽

Cited By ~ 1

Author(s):

Le Thi Khanh Hien ◽

Cuong V. Nguyen ◽

Huan Xu ◽

Canyi Lu ◽

Jiashi Feng

Keyword(s):

Convex Optimization ◽

Descent Algorithms ◽

Strongly Convex ◽

Mirror Descent ◽

Mathematical Optimization Theory and Operations Research - Lecture Notes in Computer Science ◽

On Some Methods for Strongly Convex Optimization Problems with One Functional Constraint

10.1007/978-3-030-22629-9_7 ◽

2019 ◽

pp. 82-96

Author(s):

Fedor S. Stonyakin ◽

Mohammad S. Alkousa ◽

Alexander A. Titov ◽

Victoria V. Piskunova

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Functional Constraint ◽

Strongly Convex ◽

Robustness of accelerated first-order algorithms for strongly convex optimization problems

IEEE Transactions on Automatic Control ◽

10.1109/tac.2020.3008297 ◽

2020 ◽

pp. 1-1 ◽

Cited By ~ 2

Author(s):

Hesameddin Mohammadi ◽

Meisam Razaviyayn ◽

Mihailo R. Jovanovic

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

First Order ◽

Strongly Convex ◽

Forum for Interdisciplinary Mathematics - Computational Mathematics and Applications ◽

On Modification of an Adaptive Stochastic Mirror Descent Algorithm for Convex Optimization Problems with Functional Constraints

10.1007/978-981-15-8498-5_3 ◽

2020 ◽

pp. 47-63

Author(s):

Mohammad S. Alkousa

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Functional Constraints ◽

Descent Algorithm ◽

Mirror Descent

Mirror Descent and Convex Optimization Problems with Non-smooth Inequality Constraints

Large-Scale and Distributed Optimization - Lecture Notes in Mathematics ◽

10.1007/978-3-319-97478-1_8 ◽

2018 ◽

pp. 181-213 ◽

Cited By ~ 8

Author(s):

Anastasia Bayandina ◽

Pavel Dvurechensky ◽

Alexander Gasnikov ◽

Fedor Stonyakin ◽

Alexander Titov

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Inequality Constraints ◽

Mirror Descent