Search Results - accelerated preconditions proximal gradient algorithm

Smoothing Accelerated Proximal Gradient Method with Fast Convergence Rate for Nonsmooth Convex Optimization Beyond Differentiability by Wu, Fan, Bian, Wei

“… We then introduce an error term in the SAPG algorithm to get the inexact smoothing accelerated proximal gradient algorithm…”
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A new accelerated proximal gradient technique for regularized multitask learning framework by Verma, Mridula, Shukla, K.K.

“…•A new accelerated gradient method for regularized multitask learning framework.•It is the first time that the combination of the extra-gradient and the inertial term is analyzed for Multitask learning problem…”
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Accelerated iterative hard thresholding algorithm for l0 regularized regression problem by Wu, Fan, Bian, Wei

“… We substantiate that there exists a threshold, if the extrapolation coefficients are chosen below this threshold, the proposed algorithm is equivalent to the accelerated proximal gradient algorithm…”
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Non-Rigid Structure Estimation in Trajectory Space from Monocular Vision by Wang, Yaming, Tong, Lingling, Jiang, Mingfeng, Zheng, Junbao

“… by introducing the basic low-rank condition. Moreover, the Accelerated Proximal Gradient (APG) algorithm is proposed to solve the rank minimization problem, and the initial structure matrix calculated by the PTA method is optimized…”
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New analysis of linear convergence of gradient-type methods via unifying error bound conditions by Zhang, Hui

“…This paper reveals that a common and central role, played in many error bound (EB) conditions and a variety of gradient-type methods, is a residual measure operator…”
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Distributed accelerated gradient methods with restart under quadratic growth condition by Sharma, Chhavi, Narayanan, Vishnu, Balamurugan, P.

“… Such problems are popular in distributed machine learning applications. When QGC growth parameter c is known, we propose distributed accelerated gradient methods…”
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Practical proximal primal-dual algorithms for structured saddle point problems: Practical proximal primal-dual algorithms for structured saddle point problems by Qu, Yunfei, He, Hongjin, Zhang, Tao, Han, Deren

“… By exploiting the bilinear structure of the objective, we first propose a practical accelerated Proximal Primal-Dual algorithm (PPD…”
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Bregman Proximal Gradient Algorithm With Extrapolation for a Class of Nonconvex Nonsmooth Minimization Problems by Zhang, Xiaoya, Barrio, Roberto, Martinez, M. Angeles, Jiang, Hao, Cheng, Lizhi

“… We propose a Bregman Proximal Gradient algorithm with extrapolation (BPGe). This algorithm extends and accelerates the Bregman Proximal Gradient algorithm (BPG…”
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An Accelerated Proximal Gradient Algorithm for Hankel Tensor Completion by Wang, Chuan-Long, Guo, Xiong-Wei, Yan, Xi-Hong

“…In this paper, an accelerated proximal gradient algorithm is proposed for Hankel tensor completion problems…”
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Sparse and risk diversification portfolio selection: Sparse and risk diversification portfolio selection by Li, Qian, Zhang, Wei

“…Portfolio risk management has become more important since some unpredictable factors, such as the 2008 financial crisis and the recent COVID-19 crisis…”
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The Application of the Accelerated Proximal Gradient Descent Algorithm for the Solution of the Weighted Schatten-p Norm in Sparse Noise Extraction by Wang, Jiajun, Chen, Jing, Zhu, Quanmin

“… and the weighted nuclear norm for enhanced flexibility. We adapt the model for compatibility with the Accelerated Proximal gradient descent algorithm (APG…”
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LS-Decomposition for Robust Recovery of Sensory Big Data by Liu, Xiao-Yang, Wang, Xiaodong

“…The emerging Internet of Things (IoT) systems are fueling an exponential explosion of sensory data. The major challenge to effective implementation of IoT…”
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Accelerated iterative hard thresholding algorithm for [Formula omitted] regularized regression problem by Wu, Fan, Bian, Wei

“…] regularized box constrained regression problem. We substantiate that there exists a threshold, if the extrapolation coefficients are chosen below this threshold, the proposed algorithm is equivalent to the accelerated proximal gradient algorithm…”
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VAGA: a novel viscosity-based accelerated gradient algorithm: Convergence analysis and applications by Verma, Mridula, Sahu, D. R., Shukla, K. K.

“… framework, and a recent trend is to design new accelerated algorithms to solve such frameworks efficiently. In this paper, we propose a novel viscosity-based accelerated gradient algorithm…”
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Non-convex regularization and accelerated gradient algorithm for sparse portfolio selection by Li, Qian, Zhang, Wei, Wang, Guoqiang, Bai, Yanqin

“… To solve this model, we introduce the accelerated proximal gradient…”
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Inertial accelerated stochastic mirror descent for large-scale generalized tensor CP decomposition by Liu, Zehui, Wang, Qingsong, Cui, Chunfeng, Xia, Yong

“… This paper explores generalized tensor CP decomposition, employing the Bregman distance as the proximal term and introducing an inertial accelerated block randomized stochastic mirror descent algorithm (iTableSMD…”
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On the interplay between acceleration and identification for the proximal gradient algorithm by Bareilles, Gilles, Iutzeler, Franck

“… stake; it benefits from a convergence rate that matches the one of the accelerated proximal gradient under some qualifying condition…”
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Voltage Regulation Algorithms for Multiphase Power Distribution Grids by Kekatos, Vassilis, Liang Zhang, Giannakis, Georgios B., Baldick, Ross

“… For single-phase grids, our proximal gradient scheme has computational complexity comparable to that of the rule suggested by the IEEE…”
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Adaptive restart of accelerated gradient methods under local quadratic growth condition by Fercoq, Olivier, Qu, Zheng

“…By analyzing accelerated proximal gradient methods under a local quadratic growth condition, we show that restarting these algorithms at any frequency gives a globally linearly convergent algorithm…”
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Unmatched Preconditioning of the Proximal Gradient Algorithm by Savanier, Marion, Chouzenoux, Emilie, Pesquet, Jean-Christophe, Riddell, Cyril

“…This work addresses the resolution of penalized least-squares problems using the proximal gradient algorithm (PGA…”
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