Linearized symmetric multi-block ADMM with indefinite proximal regularization and optimal proximal parameter
Sign Up to like & getrecommendations! Published in 2020 at "Calcolo"
DOI: 10.1007/s10092-020-00387-1
Abstract: The proximal term plays a significant role in the literature of proximal Alternating Direction Method of Multipliers (ADMM), since (positive-definite or indefinite) proximal terms can promote convergence of ADMM and further simplify the involved subproblems.… read more here.
Keywords: admm; proximal parameter; linearized symmetric; parameter ... See more keywords
A class of ADMM-based algorithms for three-block separable convex programming
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DOI: 10.1007/s10589-018-9994-1
Abstract: The alternating direction method of multipliers (ADMM) recently has found many applications in various domains whose models can be represented or reformulated as a separable convex minimization model with linear constraints and an objective function… read more here.
Keywords: admm; block separable; separable convex; algorithm ... See more keywords
Parallel Multi-Block ADMM with o(1 / k) Convergence
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DOI: 10.1007/s10915-016-0318-2
Abstract: This paper introduces a parallel and distributed algorithm for solving the following minimization problem with linear constraints: $$\begin{aligned} \text {minimize} ~~&f_1(\mathbf{x}_1) + \cdots + f_N(\mathbf{x}_N)\\ \text {subject to}~~&A_1 \mathbf{x}_1 ~+ \cdots + A_N\mathbf{x}_N =c,\\&\mathbf{x}_1\in {\mathcal… read more here.
Keywords: admm; parallel multi; multi block; mathbf ... See more keywords
A partially proximal S-ADMM for separable convex optimization with linear constraints
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DOI: 10.1016/j.apnum.2020.09.016
Abstract: Abstract A classical approach to solving two-block separable convex optimization could be the symmetric alternating direction method of multipliers (S-ADMM). However, its convergence may not be guaranteed for a general multi-block case without additional assumptions.… read more here.
Keywords: convex optimization; admm; proximal admm; separable convex ... See more keywords
Banded null basis and ADMM for embedded MPC
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DOI: 10.1016/j.ifacol.2017.08.2172
Abstract: Abstract In this paper, we propose an improved QP solver for embedded implementations of MPC controllers. We adopt a “reduced Hessian” approach for handling the equality constraints that arise in the well-known “banded” formulation of… read more here.
Keywords: admm; mpc; banded null; basis admm ... See more keywords
Adaptive Stochastic ADMM for Decentralized Reinforcement Learning in Edge IoT
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3187067
Abstract: Edge computing provides a promising paradigm to support the implementation of Internet of Things (IoT) by offloading tasks to nearby edge nodes. Meanwhile, the increasing network size makes it impractical for centralized data processing due… read more here.
Keywords: inline formula; edge; admm; tex math ... See more keywords
Truncated Residual Based Plug-and-Play ADMM Algorithm for MRI Reconstruction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2022.3145187
Abstract: Plug-and-play alternating direction method of multiplier (PnP-ADMM) can be used to solve the magnetic resonance imaging (MRI) reconstruction problem, which allows plugging the pre-trained denoiser to solve the denoising-like subproblem in ADMM. Many researchers explore… read more here.
Keywords: residual based; plug play; truncated residual; admm ... See more keywords
Investigating Customization Strategies and Convergence Behaviors of Task-Specific ADMM
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DOI: 10.1109/tip.2021.3113796
Abstract: Alternating Direction Method of Multiplier (ADMM) has been a popular algorithmic framework for separable optimization problems with linear constraints. For numerical ADMM fail to exploit the particular structure of the problem at hand nor the… read more here.
Keywords: convergence; admm; task; customization ... See more keywords
Learning-Aided Asynchronous ADMM for Optimal Power Flow
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Power Systems"
DOI: 10.1109/tpwrs.2021.3120260
Abstract: The synchronization requirement is a bottleneck of many distributed optimization algorithms, particularly for solving problems with computationally heterogeneous subproblems and during the occurrence of communication failure/delay. This paper presents a double-loop learning-aided asynchronous alternating direction… read more here.
Keywords: optimal power; learning aided; power flow; admm ... See more keywords
Designing Unimodular Sequences With Optimized Auto/Cross-Correlation Properties via Consensus-ADMM/PDMM Approaches
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2021.3079819
Abstract: Unimodular sequences with good auto/cross-correlation properties are favorable in wireless communication and radar applications. In this paper, we focus on designing low computational complexity but theoretically-guaranteed algorithms to achieve these kinds of sequences. The main… read more here.
Keywords: consensus; admm; correlation properties; problem ... See more keywords
A Novel Model and ADMM Algorithm for MR Image Reconstruction
Sign Up to like & getrecommendations! Published in 2018 at "Mathematical Problems in Engineering"
DOI: 10.1155/2018/5490458
Abstract: Motivated by the ideas from the LOT model and its deformations, we propose a coupling model for the MR image reconstruction and apply the split Bregman iterative method on the proposed model by utilizing the… read more here.
Keywords: admm; model; image reconstruction; proposed model ... See more keywords