Výsledky vyhľadávania - "Accelerated proximal gradient algorithm"

Adaptive accelerated proximal gradient algorithm for auto-regressive exogenous models with outliers Autor Ji, Xixi, Chen, Jing, Liu, Qiang, Zhu, Quanmin

“…This study introduces an enhanced recursive least-squares algorithm that applies the adaptive accelerated proximal gradient method to identify Auto-Regressive…”
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Accelerated proximal gradient algorithm for lithium-ion battery state of charge estimation with outliers Autor Ji, Xixi, Zhang, Zili, Mao, Yawen, Chen, Jing

“…In this paper, an accelerated proximal gradient based forgetting factor recursive least squares (APG-FFRLS) algorithm is proposed for state of charge (SOC)…”
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An Accelerated Proximal Gradient Algorithm for Hankel Tensor Completion Autor 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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An accelerated proximal gradient algorithm for source-independent waveform inversion Autor Fu, Hongsun, Ma, Mingyue, Han, Bo

“…Full Waveform Inversion (FWI) is a promising method for reconstructing subsurface parameters from the full information content in the seismogram. However, FWI…”
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One-Bit Gridless DOA Estimation with Multiple Measurements Exploiting Accelerated Proximal Gradient Algorithm Autor Tang, Wen-Gen, Jiang, Hong, Zhang, Qi

“…With low hardware cost and power consumption, direction-of-arrival (DOA) estimation exploiting one-bit quantized array data has become an attractive topic. In…”
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Electrical capacitance tomography using an accelerated proximal gradient algorithm Autor Xue, Qian, Wang, Huaxiang, Cui, Ziqiang, Yang, Chengyi

“…Image reconstruction in electrical capacitance tomography requires a solution of an ill-posed inverse problem. This paper applies an accelerated proximal…”
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An Accelerated Proximal Gradient Algorithm for Frame-Based Image Restoration via the Balanced Approach Autor Shen, Zuowei, Toh, Kim-Chuan, Yun, Sangwoon

“…Frame-based image restoration by using the balanced approach has been developed over the last decade. Many recently developed algorithms for image restoration…”
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An inexact continuation accelerated proximal gradient algorithm for low n-rank tensor recovery Autor Liu, Huihui, Song, Zhanjie

“… Furthermore, in order to solve the unconstrained nonsmooth convex optimization problem, an accelerated proximal gradient algorithm is proposed…”
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An Accelerated Proximal Gradient Algorithm for Singly Linearly Constrained Quadratic Programs with Box Constraints Autor Guo, Tiande, Zhao, Tong, Li, Mingqiang, Han, Congying

“… Hence, we propose an accelerated proximal gradient algorithm for singly linearly constrained quadratic programs with box constraints…”
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Robust support vector machine classifier with truncated loss function by gradient algorithm Autor Zhu, Wenxin, Song, Yunyan, Xiao, Yingyuan

“…The support vector machine (SVM) is an increasingly important tool in machine learning. Despite its popularity, the SVM classifier can be adversely affected…”
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Robust Lasso Regression Using Tukey's Biweight Criterion Autor Chang, Le, Roberts, Steven, Welsh, Alan

“…The adaptive lasso is a method for performing simultaneous parameter estimation and variable selection. The adaptive weights used in its penalty term mean that…”
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Identifying Heterogeneous Effect Using Latent Supervised Clustering With Adaptive Fusion Autor Chen, Jingxiang, Tran-Dinh, Quoc, Kosorok, Michael R., Liu, Yufeng

“…Precision medicine is an important area of research with the goal of identifying the optimal treatment for each individual patient. In the literature, various…”
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Homogeneity and Sparsity Pursuit Using Robust Adaptive Fused Lasso Autor Chang, Le, Shi, Yanlin

“…ABSTRACT Fused lasso regression is a popular method for identifying homogeneous groups and sparsity patterns in regression coefficients based on either the…”
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Huberized one-class support vector machine with truncated loss function in the primal space Autor Zhu, Wenxin, Song, Yunyan, Xiao, Yingyuan

“…One-class support vector machine (OCSVM) is an important tool in machine learning and has been extensively used for one-class classification problems. The…”
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Low-rank elastic-net regularized multivariate Huber regression model Autor Chen, Bingzhen, Zhai, Wenjuan, Huang, Zhiyong

“… Furthermore, an accelerated proximal gradient algorithm is designed to solve the proposed model…”
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On the penalized maximum likelihood estimation of high-dimensional approximate factor model Autor Wang, Shaoxin, Yang, Hu, Yao, Chaoli

“…In this paper, we mainly focus on the penalized maximum likelihood estimation of the high-dimensional approximate factor model. Since the current estimation…”
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Structural analysis of network traffic matrix via relaxed principal component pursuit Autor Wang, Zhe, Hu, Kai, Xu, Ke, Yin, Baolin, Dong, Xiaowen

“…The network traffic matrix is widely used in network operation and management. It is therefore of crucial importance to analyze the components and the…”
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The convergence rate of the accelerated proximal gradient algorithm for Multiobjective Optimization is faster than \(O(1/k^2)\) Autor Zhang, Jie, Yang, Xinmin

“…In this paper, we propose a fast proximal gradient algorithm for multiobjective optimization, it is proved that the convergence rate of the accelerated…”
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Efficient 2D adaptive beamforming algorithm based on sparse array optimisation Autor Wang, Chaoyu, Zhu, Can, Chen, Chunlin, Li, Hongtao

“… received signal matrix, genetic algorithm is used to optimise the sparse sampling array. Thirdly, the accelerated proximal gradient algorithm is adopted to reconstruct the complete received signal matrix…”
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Constrained Cramér-Rao Bound on Robust Principal Component Analysis Autor Gongguo Tang, Nehorai, Arye

“…We investigate the behavior of the mean-square error (MSE) of low-rank and sparse matrix decomposition, in particular the special case of the robust principal…”
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