Results 191 to 200 of about 16,083 (234)

A survey on applications of Alternating Direction Method of Multipliers in smart power grids

Renewable & Sustainable Energy Reviews, 2021
Optimization algorithms play a significant role in the optimal solution of various problems in Smart Grid. Distributed algorithms are of considerable research interest as these algorithms replace the centrally computed algorithms.
A. Maneesha, K. Swarup
semanticscholar   +1 more source

Transmit beamspace design for FDA-MIMO radar with alternating direction method of multipliers

Signal Processing, 2021
Hybridization of a frequency diverse array (FDA) generated range-angle-time dependent beampattern with multiple input multiple output (MIMO) radar waveform diversity, namely, FDA-MIMO radar, provides more degrees-of-freedom to improve overall system ...
A. Basit, Wen-qin Wang, Samad Wali, S. Y. Nusenu   +3 more
semanticscholar   +1 more source

Robust Minimum Variance Beamforming With Sidelobe-Level Control Using the Alternating Direction Method of Multipliers

IEEE Transactions on Aerospace and Electronic Systems, 2021
Adaptive beamforming with sidelobe-level control in the presence of signal steering vector uncertainty is investigated. Unlike the traditional multiconstrained optimization strategy using the interior point method, iterative optimization algorithms with ...
Wenxia Wang, Shefeng Yan, Linlin Mao, Xiangyu Guo   +3 more
semanticscholar   +1 more source

Convergence Rate Analysis for the Alternating Direction Method of Multipliers with a Substitution Procedure for Separable Convex Programming

Mathematics of Operations Research, 2017
© 2017 INFORMS. Recently, in He et al. [He BS, Tao M, Yuan XM (2012) Alternating direction method with Gaussian back substitution for separable convex programming. SIAM J. Optim.
Min Tao, Xiaoming Yuan
exaly   +2 more sources

A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers

European Conference on Computer Vision, 2018
Weight pruning methods for deep neural networks (DNNs) have been investigated recently, but prior work in this area is mainly heuristic, iterative pruning, thereby lacking guarantees on the weight reduction ratio and convergence time.
Tianyun Zhang, Shaokai Ye, Kaiqi Zhang, Jian Tang, Wujie Wen, M. Fardad, Yanzhi Wang   +6 more
semanticscholar   +1 more source

A Penalty Alternating Direction Method of Multipliers for Convex Composite Optimization Over Decentralized Networks

IEEE Transactions on Signal Processing, 2021
Consider the problem of minimizing a sum of convex composite functions over a decentralized network, where each agent in the network holds a private function consisting of a smooth part and a nonsmooth part, and it can only exchange information with its ...
Jiaojiao Zhang, Huikang Liu, A. M. So, Qing Ling   +3 more
semanticscholar   +1 more source

Iterative reconstruction for low dose CT using Plug-and-Play alternating direction method of multipliers (ADMM) framework

Medical Imaging 2019: Image Processing, 2019
Concerns over the risks of radiation dose from diagnostic CT motivated the utilization of low dose CT (LdCT). However, due to the extremely low X-ray photon statistics in LdCT, the reconstruction problem is ill-posed and noisecontaminated. Conventional Compressed Sensing (CS) methods have been investigated to enhance the signal-to-noise ratio of LdCT ...
Qihui Lyu, Dan Ruan, John M. Hoffman, Ryan Neph, Michael F. McNitt-Gray, Ke Sheng   +5 more
openaire   +1 more source

Solving variational inequalities and cone complementarity problems in nonsmooth dynamics using the alternating direction method of multipliers

International Journal for Numerical Methods in Engineering, 2021
This work presents a numerical method for the solution of variational inequalities arising in nonsmooth flexible multibody problems that involve set‐valued forces.
A. Tasora, D. Mangoni, Simone Benatti, R. Garziera   +3 more
semanticscholar   +1 more source

A Riemannian Alternating Direction Method of Multipliers

Mathematics of Operations Research
We consider a class of Riemannian optimization problems where the objective is the sum of a smooth function and a nonsmooth function considered in the ambient space.
Jiaxiang Li, Shiqian Ma, Tejes Srivastava   +2 more
semanticscholar   +1 more source

Robust and Sparse Linear Discriminant Analysis via an Alternating Direction Method of Multipliers

IEEE Transactions on Neural Networks and Learning Systems, 2020
In this paper, we propose a robust linear discriminant analysis (RLDA) through Bhattacharyya error bound optimization. RLDA considers a nonconvex problem with the $L_{1}$ -norm operation that makes it less sensitive to outliers and noise than the $L_{2}
Chunna Li, Y. Shao, W. Yin, Ming-Zeng Liu   +3 more
semanticscholar   +1 more source