Results 211 to 220 of about 1,485 (240)

A partially proximal linearized alternating minimization method for finding Dantzig selectors

Computational and Applied Mathematics, 2021
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Xiaoyu Mao, Hongjin He, Hong-Kun Xu
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A proximal alternating direction method of multipliers for a minimization problem with nonconvex constraints

Journal of Global Optimization, 2015
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Jianli Chen, Wenxing Zhu, Zheng Peng
exaly   +2 more sources

Alternating Proximal Gradient Method for Convex Minimization

Journal of Scientific Computing, 2015
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exaly   +4 more sources

A New Class of Alternating Proximal Minimization Algorithms with Costs-to-Move

SIAM Journal on Optimization, 2007
Given two objective functions $f:\mathcal X\mapsto\R\cup\{+\infty\}$ and $g:\mathcal Y\mapsto\R\cup\{+\infty\}$ on abstract spaces $\mathcal X$ and $\mathcal Y$, and a coupling function $c:\mathcal X\times\mathcal Y\mapsto\R^+$, we introduce and study alternative minimization algorithms of the following type: $(x_0,y_0)\in\mathcal X\times\mathcal Y ...
H Attouch
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A generalized inertial proximal alternating linearized minimization method for nonconvex nonsmooth problems

Applied Numerical Mathematics, 2023
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Deren Han
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Proximal Alternating Minimization for Analysis Dictionary Learning and Convergence Analysis

IEEE Transactions on Emerging Topics in Computational Intelligence, 2018
The sparse analysis model is an alternative approach to the sparse synthesis model that has emerged recently. Most analysis dictionary learning problems based on the sparse analysis model require solving a class of challenging nonsmooth and even nonconvex optimization problems.
Zhenni Li, Shuxue Ding, Zuyuan Yang
exaly   +2 more sources

Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality [PDF]

Mathematics of Operations Research, 2010
We study the convergence properties of an alternating proximal minimization algorithm for nonconvex structured functions of the type: L(x,y)=f(x)+Q(x,y)+g(y), where f and g are proper lower semicontinuous functions, defined on Euclidean spaces, and Q is a smooth function that couples the variables x and y.
Jérôme Bolte, Antoine Soubeyran, Hedy ATTOUCH   +2 more
exaly   +5 more sources

Adaptive total variation based image segmentation with semi-proximal alternating minimization

Signal Processing, 2021
Abstract To improve the image segmentation quality, it is important to adequately describe the local features of targets in images. In this paper, we develop a novel adaptive total variation based two-stage segmentation approach to restore and segment images under complex degradations.
Tingting Wu 0001, Xiaoyu Gu, Youguo Wang, Tieyong Zeng   +3 more
openaire   +1 more source

A proximal alternating minimization algorithm for the largest C-eigenvalue of piezoelectric-type tensors

Journal of Global Optimization, 2022
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Wenjie Wang, Haibin Chen, Yiju Wang, Guanglu Zhou   +3 more
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A Proximal Alternating Direction Method for Semi-Definite Rank Minimization

Proceedings of the AAAI Conference on Artificial Intelligence, 2016
Semi-definite rank minimization problems model a wide range of applications in both signal processing and machine learning fields. This class of problem is NP-hard in general. In this paper, we propose a proximal Alternating Direction Method (ADM) for the well-known semi-definite rank regularized minimization problem.
Ganzhao Yuan, Bernard Ghanem
openaire   +2 more sources