A truncated nuclear norm and graph-Laplacian regularized low-rank representation method for tumor clustering and gene selection [PDF]
BMC Bioinformatics, 2022 Background Clustering and feature selection act major roles in many communities. As a matrix factorization, Low-Rank Representation (LRR) has attracted lots of attentions in clustering and feature selection, but sometimes its performance is frustrated ...
Qi Liu
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Nuclear Norm Regularized Deep Neural Network for EEG-Based Emotion Recognition [PDF]
Frontiers in Psychology, 2022 Electroencephalography (EEG) based emotion recognition enables machines to perceive users' affective states, which has attracted increasing attention.
Shuang Liang +5 more
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Predict potential miRNA-disease associations based on bounded nuclear norm regularization [PDF]
Frontiers in Genetics, 2022 Increasing evidences show that the abnormal microRNA (miRNA) expression is related to a variety of complex human diseases. However, the current biological experiments to determine miRNA-disease associations are time consuming and expensive.
Yidong Rao, Minzhu Xie, Hao Wang
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A Joint Fault Diagnosis Scheme Based on Tensor Nuclear Norm Canonical Polyadic Decomposition and Multi-Scale Permutation Entropy for Gears [PDF]
Entropy, 2018 Gears are key components in rotation machinery and its fault vibration signals usually show strong nonlinear and non-stationary characteristics. It is not easy for classical time–frequency domain analysis methods to recognize different gear working ...
Mao Ge +4 more
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Discovering Temporal Patterns in Longitudinal Nontargeted Metabolomics Data via Group and Nuclear Norm Regularized Multivariate Regression [PDF]
Metabolites, 2020 Temporal associations in longitudinal nontargeted metabolomics data are generally ignored by common pattern recognition methods such as partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS ...
Zhaozhou Lin +3 more
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A lagrange programming neural network approach for nuclear norm optimization. [PDF]
PLoS ONEThis article proposes a continuous-time optimization approch instead of tranditional optimiztion methods to address the nuclear norm minimization (NNM) problem.
Xiangguang Dai +3 more
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Norm-Attaining Tensors and Nuclear Operators [PDF]
Mediterranean Journal of Mathematics, 2022 25 pages.
Sheldon Dantas +3 more
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Mixed Noise Removal Using Adaptive Median Based Non-Local Rank Minimization
IEEE Access, 2021 In this paper, we present an innovative mechanism for image restoration problems in which the image is corrupted by a mixture of additive white Gaussian noise (AWGN) and impulse noise (IN). Mixed noise removal is much more challenging problem in contrast
Dai-Gyoung Kim +5 more
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Connections Between Nuclear-Norm and Frobenius-Norm-Based Representations [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2018 A lot of works have shown that frobenius-norm based representation (FNR) is competitive to sparse representation and nuclear-norm based representation (NNR) in numerous tasks such as subspace clustering. Despite the success of FNR in experimental studies, less theoretical analysis is provided to understand its working mechanism.
Xi Peng, Canyi Lu, Zhang Yi, Huajin Tang
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Application of Weighted Truncated p Norm in Motion Target Detection [PDF]
Jisuanji gongcheng, 2018 In the moving object detection methods base on low rank and sparse decomposition,the nuclear norm is not the best approximation of the rank function of the matrix,meanwhile,the spatial continuity of moving object is not to be considered.As a result,the ...
XUAN Xiao,YU Qin
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