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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Drug-target interaction prediction using Multi Graph Regularized Nuclear Norm Minimization. [PDF]
PLoS ONE, 2020 The identification of potential interactions between drugs and target proteins is crucial in pharmaceutical sciences. The experimental validation of interactions in genomic drug discovery is laborious and expensive; hence, there is a need for efficient ...
Aanchal Mongia, Angshul Majumdar
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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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Predicting human miRNA disease association with minimize matrix nuclear norm [PDF]
Scientific ReportsmicroRNAs (miRNAs) are non-coding RNA molecules that influence the development and progression of many diseases. Research have documented that miRNAs have a significant role in the prevention, diagnosis, and treatment of complex human diseases. Recently,
Ahmet Toprak
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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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Double Structured Nuclear Norm-Based Matrix Decomposition for Saliency Detection
IEEE Access, 2020 Saliency detection aims at identifying the most important and informative area in a scene. Recently low rank matrix recovery (LR) theory becomes an effective tool for saliency detection.
Junxia Li, Ziyang Wang, Zefeng Pan
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