Results 111 to 120 of about 7,185 (222)
ADMM Decoding of LDPC Codes: Simplification and Improvement
, 2021 In this dissertation, we study linear programming (LP) decoding of low-density parity-check (LDPC) codes based on the alternating direction method of multipliers (ADMM) technique, or ADMM decoding for short. The decoding of LDPC codes is formulated as an
Wei, Haoyuan
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A Decentralized ADMM-Cauchy Framework for Enhancing Dynamic Economic Dispatch in Power Networks
Journal of Electrical and Computer EngineeringAddressing the challenges of dynamic economic dispatch (DED) in modern power systems, this paper introduces a distributed alternating direction method of multipliers with Cauchy convergence framework (ADMM-Cauchy).
Yaming Ren
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Sparse Optimization of Vibration Signal by ADMM [PDF]
Journal of Applied Mathematics, 2017 In this paper, the alternating direction method of multipliers (ADMM) algorithm is applied to the compressed sensing theory to realize the sparse optimization of vibration signal. Solving the basis pursuit problem for minimizing theL1norm minimization under the equality constraints, the sparse matrix obtained by the ADMM algorithm can be reconstructed ...
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Differentially Private ADMM for Regularized Consensus Optimization
, 2020 Due to its broad applicability in machine learning, resource allocation, and control, the alternating direction method of multipliers (ADMM) has been extensively studied in the literature.
Zhang, Junshan +3 more
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Fast Stochastic Variance Reduced ADMM for Stochastic Composition Optimization
, 2017 We consider the stochastic composition optimization problem proposed in \cite{wang2017stochastic}, which has applications ranging from estimation to statistical and machine learning.
Longbo Huang, Yue Yu
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Distributed Inexact Consensus-Based ADMM Method for Multi-Agent Unconstrained Optimization Problem
IEEE Access, 2019 Recently, the alternating direction method of multipliers (ADMM) has been used effectively to solve the multi-agent unconstrained optimization problems, where the objective function is the sum of privately known local objective functions of agents.
Long Jian +3 more
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Journal of Inequalities and Applications, 2017 The proximal alternating direction method of multipliers (P-ADMM) is an efficient first-order method for solving the separable convex minimization problems. Recently, He et al.
Min Sun, Jing Liu
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Convergence of Nonconvex PnP-ADMM with MMSE Denoisers
, 2023 Plug-and-Play Alternating Direction Method of Multipliers (PnP-ADMM) is a widely-used algorithm for solving inverse problems by integrating physical measurement models and convolutional neural network (CNN) priors.
Gan, Weijie +3 more
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Fast-Converging Decentralized ADMM for Consensus Optimization
For its well-established convergence properties and applicability to various optimization problems, the alternating direction method of multipliers (ADMM) has been at the center of several research fields.
He, Jeannie, +2 more
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Fast-converging decentralized alternating direction method of multipliers for consensus optimization
EURASIP Journal on Advances in Signal ProcessingFor its well-established convergence properties, simplicity, and applicability to various optimization problems, the alternating direction method of multipliers (ADMM) has been at the center of several research fields.
Jeannie He, Ming Xiao, Mikael Skoglund
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