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SIAM Journal on Optimization, ISSN 1052-6234, 2016, Volume 26, Issue 1, pp. 337 - 364
The alternating direction method of multipliers (ADMM) is widely used to solve large-scale linearly constrained optimization problems, convex or nonconvex, in... 
Nonconvex optimization | Sharing | ADMM | Consensus | consensus | MATHEMATICS, APPLIED | nonconvex optimization | ALGORITHMS | sharing
Journal Article
SIAM Journal on Optimization, ISSN 1052-6234, 2015, Volume 25, Issue 2, pp. 882 - 915
In this paper, we consider conic programming problems whose constraints consist of linear equalities, linear inequalities, a nonpolyhedral cone, and a... 
Semiproximal ADMM | Multiblock ADMM | Conic programming | SDP | Convergence | MATHEMATICS, APPLIED | conic programming | GAUSSIAN BACK SUBSTITUTION | semiproximal ADMM | convergence | DECOMPOSITION METHOD | ALGORITHM | RANK | SEMIDEFINITE | PENALTY | multiblock ADMM | RELAXATIONS | SPLITTING METHOD
Journal Article
Neurocomputing, ISSN 0925-2312, 09/2019
Journal Article
by Lu, CY and Feng, JS and Yan, SC and Lin, ZC
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, ISSN 0162-8828, 03/2018, Volume 40, Issue 3, pp. 527 - 541
Accompanied with the rising popularity of compressed sensing, the Alternating Direction Method of Multipliers (ADMM) has become the most widely used solver for... 
GRAPH | Unified frameworks of ADMM | mixed ADMM | ALGORITHM | convex optimization | CONVERGENCE RATE | majorization minimization | LOW-RANK | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 11/2018, pp. 1 - 1
Compressive sensing (CS) is an effective technique for reconstructing image from a small amount of sampled data. It has been widely applied in medical imaging,... 
deep learning | Compressive sensing | Imaging | Transforms | Computer architecture | Data models | MR Imaging | Task analysis | ADMM | ADMM-CSNet | Image reconstruction
Journal Article
IEEE Transactions on Medical Imaging, ISSN 0278-0062, 06/2017, Volume 36, Issue 6, pp. 1326 - 1336
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 12/2019, Volume 28, Issue 12, pp. 6211 - 6224
In image processing, total variation (TV) regularization models are commonly used to recover the blurred images. One of the most efficient and popular methods... 
Kurdyka-Łojasiewicz property | nonconvex method | Inertial algorithms | Minimization | image deblurring | Convex functions | inertial proximal ADMM | Image restoration | Indexes | ADMM | Convergence
Journal Article
International Journal of Control, ISSN 0020-7179, 04/2017, pp. 1 - 11
Journal Article
IEEE Transactions on Smart Grid, ISSN 1949-3053, 07/2017, Volume 8, Issue 4, pp. 1852 - 1863
One of the main challenges for electric vehicle (EV) aggregators is the definition of a control infrastructure that scales to large EV numbers. This paper... 
Jacobian matrices | smart grid | Scalability | Benchmark testing | Electric vehicles | Cost function | Convex functions | ADMM | Optimization | distributed computing | electric vehicles | CAPACITY | DEMAND | CHARGING CONTROL | ALGORITHM | D-ADMM | ENGINEERING, ELECTRICAL & ELECTRONIC | Computational geometry | Charging | Multipliers | Convexity | Distributing | Electric power distribution | Versatility
Journal Article
Pattern Recognition, ISSN 0031-3203, 02/2020, Volume 98, p. 107058
Calibration and localisation of a camera sensor network is an essential requirement for higher-level computer vision tasks, such as mapping or tracking.... 
Localisation | Distributed algorithms | ADMM | Multi-view calibration | Gaussian belief propagation
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 07/2019, Volume 41, Issue 7, pp. 1695 - 1708
Journal Article
2018 52nd Asilomar Conference on Signals, Systems, and Computers, ISSN 1058-6393, 10/2018, Volume 2018-, pp. 1881 - 1885
Distributed optimization has gained popularity in many areas because it can to cope with the increasing volume of data, and the corresponding demand for... 
Network topology | decentralized optimization | weighted ADMM | Optimized production technology | Cost function | Convex functions | Topology | hybrid ADMM | ADMM | Convergence
Conference Proceeding
SIAM Journal on Scientific Computing, ISSN 1064-8275, 2017, Volume 39, Issue 3, pp. B548 - B570
Journal Article
Information Sciences, ISSN 0020-0255, 01/2020, Volume 507, pp. 185 - 196
In this paper, we consider the distributed optimization problem, where the objective function is the sum of local cost functions. To solve this problem, a new... 
ADMM | Distributed optimization | Parallel algorithm | Analysis | Methods | Algorithms
Journal Article
Signal Processing, ISSN 0165-1684, 02/2020, Volume 167, p. 107296
In this paper, an optimization algorithm based on the alternating direction method of multipliers (ADMM) is proposed for robust sparse channel estimation in... 
[formula omitted] optimization problem | ADMM | OFDM systems | Sparse channel estimation
Journal Article
Signal Processing, ISSN 0165-1684, 02/2020, Volume 167, p. 107319
Journal Article
IEEE Transactions on Automatic Control, ISSN 0018-9286, 09/2019, Volume 64, Issue 9, pp. 3869 - 3876
Journal Article
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