Convergence of a generalized subgradient method for nondifferentiable convex optimization

Mathematical Programming ◽

10.1007/bf01594925 ◽

1991 ◽

Vol 50 (1-3) ◽

pp. 75-80 ◽

Author(s):

Sehun Kim ◽

Hyunsil Ahn

Keyword(s):

Convex Optimization ◽

Subgradient Method

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An interior-point based subgradient method for nondifferentiable convex optimization

Optimization Methods and Software ◽

10.1080/10556789808805711 ◽

1998 ◽

Vol 10 (2) ◽

pp. 197-215

Author(s):

J. B. G. Frenk ◽

J. F. Sturm ◽

S. Zhang

Keyword(s):

Convex Optimization ◽

Interior Point ◽

Subgradient Method

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Interior quasi-subgradient method with non-Euclidean distances for constrained quasi-convex optimization problems in hilbert spaces

Journal of Global Optimization ◽

10.1007/s10898-021-01110-2 ◽

2021 ◽

Author(s):

Regina S. Burachik ◽

Yaohua Hu ◽

Xiaoqi Yang

Keyword(s):

Convex Optimization ◽

Hilbert Spaces ◽

Optimization Problems ◽

Subgradient Method ◽

Convex Optimization Problems ◽

Euclidean Distances

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Distributed Event-Triggered Subgradient Method for Convex Optimization with a Common Constraint Set

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2017.08.2449 ◽

2017 ◽

Vol 50 (1) ◽

pp. 15319-15324 ◽

Author(s):

Yuichi Kajiyama ◽

Naoki Hayashi ◽

Shigemasa Takai

Keyword(s):

Convex Optimization ◽

Subgradient Method ◽

Constraint Set ◽

Event Triggered

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A Randomized Block Coordinate Iterative Regularized Subgradient Method for High-dimensional Ill-posed Convex Optimization

2019 American Control Conference (ACC) ◽

10.23919/acc.2019.8815256 ◽

2019 ◽

Author(s):

Harshal Kaushik ◽

Farzad Yousefian

Keyword(s):

Convex Optimization ◽

Subgradient Method ◽

High Dimensional ◽

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On the projected subgradient method for nonsmooth convex optimization in a Hilbert space

Mathematical Programming ◽

10.1007/bf01584842 ◽

1998 ◽

Vol 81 (1) ◽

pp. 23-35 ◽

Author(s):

Ya. I. Alber ◽

A. N. Iusem ◽

M. V. Solodov

Keyword(s):

Hilbert Space ◽

Convex Optimization ◽

Subgradient Method ◽

Nonsmooth Convex Optimization

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The Projected Subgradient Method for Nonsmooth Convex Optimization in the Presence of Computational Errors

Numerical Functional Analysis and Optimization ◽

10.1080/01630563.2010.489248 ◽

2010 ◽

Vol 31 (5) ◽

pp. 616-633 ◽

Author(s):

Alexander J. Zaslavski

Keyword(s):

Convex Optimization ◽

Subgradient Method ◽

Nonsmooth Convex Optimization ◽

Computational Errors

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On Distributed Non-convex Optimization: Projected Subgradient Method For Weakly Convex Problems in Networks

IEEE Transactions on Automatic Control ◽

10.1109/tac.2021.3056535 ◽

2021 ◽

pp. 1-1

Author(s):

Shixiang Chen ◽

Alfredo Garcia ◽

Shahin Shahrampour

Keyword(s):

Convex Optimization ◽

Subgradient Method ◽

Weakly Convex ◽

Convex Problems

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Subgradient method with feasible inexact projections for constrained convex optimization problems

Optimization ◽

10.1080/02331934.2021.1902520 ◽

2021 ◽

pp. 1-23

Author(s):

A. A. Aguiar ◽

O. P. Ferreira ◽

L. F. Prudente

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Subgradient Method ◽

Convex Optimization Problems ◽

Constrained Convex Optimization

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Incremental subgradient method for nonsmooth convex optimization with fixed point constraints

Optimization Methods and Software ◽

10.1080/10556788.2016.1175002 ◽

2016 ◽

Vol 31 (5) ◽

pp. 931-951 ◽

Author(s):

H. Iiduka

Keyword(s):

Fixed Point ◽

Convex Optimization ◽

Subgradient Method ◽

Nonsmooth Convex Optimization

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A Subgradient Method Based on Gradient Sampling for Solving Convex Optimization Problems

Numerical Functional Analysis and Optimization ◽

10.1080/01630563.2015.1086788 ◽

2015 ◽

Vol 36 (12) ◽

pp. 1559-1584 ◽

Author(s):

Yaohua Hu ◽

Chee-Khian Sim ◽

Xiaoqi Yang

Keyword(s):

Convex Optimization ◽

Optimization Problems ◽

Subgradient Method ◽

Gradient Sampling ◽

Convex Optimization Problems

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