Results 41 to 50 of about 3,085 (135)

The symmetric ADMM with indefinite proximal regularization and its application

Journal of Inequalities and Applications, 2017
Due to updating the Lagrangian multiplier twice at each iteration, the symmetric alternating direction method of multipliers (S-ADMM) often performs better than other ADMM-type methods.
Hongchun Sun, Maoying Tian, Min Sun
doaj   +1 more source

Linear Convergence Rate of Splitting Algorithms for Multi-Block Constrained Convex Minimizations

IEEE Access, 2020
Multi-block linear constrained separable convex minimizations are ubiquitous and have been drawing increasing attention in recent researches. The alternating direction method of multipliers (ADMM) has been well studied and used in the literature for the ...
Xiaoge Deng, Feng Liu, Feng Huang
doaj   +1 more source

ADMM-SVNet: An ADMM-Based Sparse-View CT Reconstruction Network

Photonics, 2022
In clinical medical applications, sparse-view computed tomography (CT) imaging is an effective method for reducing radiation doses. The iterative reconstruction method is usually adopted for sparse-view CT.
Sukai Wang, Xuan Li, Ping Chen
doaj   +1 more source

Toward Encrypted OPF Across Transmission and Distribution—Prospects and Open Problems of Encrypted Quadratic Programming

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT The increasing integration of distributed energy resources demands enhanced coordination between transmission system operators (TSOs) and distribution system operators (DSOs) to maintain reliable grid operation. Traditional approaches rely on hierarchical or distributed optimization schemes for power flow management, but these methods either ...
Janis Adamek, Philipp Binfet, Maísa Beraldo Bandeira, Timm Faulwasser, Moritz Schulze Darup   +4 more
wiley   +1 more source

Initial State Privacy of Nonlinear Systems on Riemannian Manifolds

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley   +1 more source

Regularized extreme learning machine based on variable step alternating direction method of multipliers

Shenzhen Daxue xuebao. Ligong ban
To address the deficiency of slow convergence rate and stagnation of error decay during later iteration of alternating direction method of multipliers (ADMM) for regularized extreme learning machine (RELM), we propose a dynamic step size ADMM-based RELM ...
LU Huihuang, ZOU Weidong, LI Yuxiang
doaj   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang, Jian Yang, Bob Zhang, Yang Tang, Wenli Du, Bihan Wen   +5 more
wiley   +1 more source

Optimizing linear energy transfer distribution in intensity-modulated proton therapy using the alternating direction method of multipliers

Frontiers in Oncology
PurposeThis study develop a novel linear energy transfer (LET) optimization method for intensity-modulated proton therapy (IMPT) with minimum monitor unit (MMU) constraint using the alternating direction method of multipliers (ADMM).Material and ...
Qingkun Fan, Xiaoyuan Zhang, Riao Dao, Yujia Qian, Lewei Zhao, Xiaoqiang Li, Xuanfeng Ding, Gang Liu, Gang Liu, Shuyang Dai, Shuyang Dai   +10 more
doaj   +1 more source

On the Convergence of Bregman ADMM With Variational Inequality

IEEE Access, 2020
The alternating direction method of multipliers (ADMM) is one of most foundational algorithms for linear constrained composite minimization problems. For different specific problems, variations of ADMM (like linearized ADMM, proximal ADMM) are developed.
Peibing Du, Hao Jiang
doaj   +1 more source

Flexibility Feasible Region Construction and Operation Optimization for Urban Residential Smart Buildings

IET Smart Energy Systems, EarlyView.
To effectively harness the flexibility of urban residential buildings, this study proposes using the feasible flexibility region (FFR) of residential smart buildings (RSB) as an alternative to directly scheduling a large number of diverse, dispersed, and heterogeneous flexibility resources.
Youjun Deng, Fengji Luo, Yongxi Zhang, Anan Zhang   +3 more
wiley   +1 more source