Suchergebnisse - "proximal alternating minimization algorithm"

A proximal alternating minimization algorithm for the largest C-eigenvalue of piezoelectric-type tensors von Wang, Wenjie, Chen, Haibin, Wang, Yiju, Zhou, Guanglu

“… C-eigenvalues of piezoelectric-type tensors play an important role in piezoelectric effect and converse piezoelectric effect. While the largest C-eigenvalue of …”
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A Learned Proximal Alternating Minimization Algorithm and Its Induced Network for a Class of Two-Block Nonconvex and Nonsmooth Optimization von Chen, Yunmei, Liu, Lezhi, Zhang, Lei

“… This work proposes a general learned proximal alternating minimization algorithm, LPAM, for solving learnable two-block nonsmooth and nonconvex optimization problems …”
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The Proximal Alternating Minimization Algorithm for Two-Block Separable Convex Optimization Problems with Linear Constraints von Bitterlich, Sandy, Boţ, Radu Ioan, Csetnek, Ernö Robert, Wanka, Gert

“… The Alternating Minimization Algorithm has been proposed by Paul Tseng to solve convex programming problems with two-block separable linear constraints and …”
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Linearized proximal alternating minimization algorithm for motion deblurring by nonlocal regularization von Yun, Sangwoon, Woo, Hyenkyun

“… Non-blind motion deblurring problems are highly ill-posed and so it is quite difficult to find the original sharp and clean image. To handle ill-posedness of …”
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Learnable Spatial-Spectral Transform-Based Tensor Nuclear Norm for Multi-Dimensional Visual Data Recovery von Liu, Sheng, Leng, Jinsong, Zhao, Xi-Le, Zeng, Haijin, Wang, Yao, Yang, Jing-Hua

“… Recently, transform-based tensor nuclear norm (TNN) methods have received increasing attention as a powerful tool for multi-dimensional visual data (color …”
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Tensor completion via total curvature variation and low-rank matrix factorization von Xu, Zhi, Yang, Jing-Hua, Zhao, Xi-Le, Yan, Xi-hong, Wang, Chuan-long

“… Curvature-based regularization has attracted growing concern in the field of image restoration, benefiting from its favorable geometric properties, such as …”
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A Learned Proximal Alternating Minimization Algorithm and Its Induced Network for a Class of Two-block Nonconvex and Nonsmooth Optimization von Chen, Yunmei, Liu, Lezhi, Zhang, Lei

“… This work proposes a general learned proximal alternating minimization algorithm, LPAM, for solving learnable two-block nonsmooth and nonconvex optimization problems …”
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The Proximal Alternating Minimization Algorithm for two-block separable convex optimization problems with linear constraints von Bitterlich, Sandy, Bot, Radu Ioan, Ernö Robert Csetnek, Wanka, Gert

“… The Alternating Minimization Algorithm (AMA) has been proposed by Tseng to solve convex programming problems with two-block separable linear constraints and …”
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Hyperspectral Images Mixed Noise Removal via Group-Tube Transform Induced Collaborative Sparsity and Low-Rankness von Li, Ben-Zheng, Ji, Teng-Yu, Wang, Jian-Li

“… The transform-based tensor nuclear norm (TNN) methods have shown promise in hyperspectral images (HSIs) mixed noise removal. However, these transform-based …”
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Tensor Completion via Complementary Global, Local, and Nonlocal Priors von Zhao, Xi-Le, Yang, Jing-Hua, Ma, Tian-Hui, Jiang, Tai-Xiang, Ng, Michael K., Huang, Ting-Zhu

“… Completing missing entries in multidimensional visual data is a typical ill-posed problem that requires appropriate exploitation of prior information of the …”
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Dictionary Learning With Low-Rank Coding Coefficients for Tensor Completion von Jiang, Tai-Xiang, Zhao, Xi-Le, Zhang, Hao, Ng, Michael K.

“… In this article, we propose a novel tensor learning and coding model for third-order data completion. The aim of our model is to learn a data-adaptive …”
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Hyperspectral and Multispectral Image Fusion Using Factor Smoothed Tensor Ring Decomposition von Chen, Yong, Zeng, Jinshan, He, Wei, Zhao, Xi-Le, Huang, Ting-Zhu

“… Fusing a pair of low-spatial-resolution hyperspectral image (LR-HSI) and high-spatial-resolution multispectral image (HR-MSI) has been regarded as an effective …”
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Imbalanced low-rank tensor completion via latent matrix factorization von Qiu, Yuning, Zhou, Guoxu, Zeng, Junhua, Zhao, Qibin, Xie, Shengli

“… Tensor completion has been widely used in computer vision and machine learning. Most existing tensor completion methods empirically assume the intrinsic tensor …”
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Tensor train rank minimization with hybrid smoothness regularization for visual data recovery von Yang, Jing-Hua, Zhao, Xi-Le, Ma, Tian-Hui, Ding, Meng, Huang, Ting-Zhu

“… We develop an efficient proximal alternating minimization algorithm to solve the proposed new model with guaranteed convergence …”
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A New Multiplicative Denoising Variational Model Based on mth Root Transformation von YUN, Sangwoon, WOO, Hyenkyun

“… In coherent imaging systems, such as the synthetic aperture radar (SAR), the observed images are contaminated by multiplicative noise. Due to the …”
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Inertial proximal alternating minimization for nonconvex and nonsmooth problems von Zhang, Yaxuan, He, Songnian

“… We present a proximal alternating minimization algorithm with inertial effect. We obtain the convergence by constructing a key function H that guarantees a sufficient decrease property of the iterates …”
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Poisson Tensor Completion via Nonconvex Regularization and Nonlocal Self-Similarity for Multi-dimensional Image Recovery von Qiu, Duo, Xia, Sijia, Yang, Bei, Li, Bo, Zhang, Xiongjun

“… The problem of Poisson tensor completion aims to recover a tensor from partial observations in the presence of Poisson noise. Existing approaches utilized the …”
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Spatiotemporal traffic data imputation by synergizing low tensor ring rank and nonlocal subspace regularization von Wu, Peng‐Ling, Ding, Meng, Zheng, Yu‐Bang

“… Spatiotemporal traffic data usually suffers from missing entries in the data acquisition and transmission process. Existing imputation methods only consider …”
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Tensor ring decomposition-based model with interpretable gradient factors regularization for tensor completion von Wu, Peng-Ling, Zhao, Xi-Le, Ding, Meng, Zheng, Yu-Bang, Cui, Lu-Bin, Huang, Ting-Zhu

“… Tensor ring (TR) decomposition, which factorizes a tensor into a sequence of cyclically interconnected third-order TR factors, is a powerful tool to capture …”
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A structure noise-aware tensor dictionary learning method for high-dimensional data clustering von Yang, Jing-Hua, Chen, Chuan, Dai, Hong-Ning, Fu, Le-Le, Zheng, Zibin

“… With the development of data acquisition technology, high-dimensional data clustering is an important yet challenging task in data mining. Despite advances …”
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