Výsledky vyhledávání - "accelerated proximal gradient algorithm"

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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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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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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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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Low-rank elastic-net regularized multivariate Huber regression model Autor Chen, Bingzhen, Zhai, Wenjuan, Huang, Zhiyong

“…Heavy-tailed noise or strongly correlated predictors often go with the multivariate linear regression model. To tackle with these problems, this paper focuses…”
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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. In our method, the iterative completion tensors…”
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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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Efficient 2D adaptive beamforming algorithm based on sparse array optimisation Autor Wang, Chaoyu, Zhu, Can, Chen, Chunlin, Li, Hongtao

“…In this study, a 2D adaptive beamforming algorithm for sparse array is proposed. Firstly, a signal model based on matrix completion theory for adaptive…”
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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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Image Restoration with Mixed or Unknown Noises Autor Gong, Zheng, Shen, Zuowei, Toh, Kim-Chuan

“…This paper proposes a simple model for image restoration with mixed or unknown noises. It can handle image restoration without assuming any prior knowledge of…”
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