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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GPR Clutter Removal Based on Weighted Nuclear Norm Minimization for Nonparallel Cases [PDF]
Sensors, 2023 Ground-penetrating radar (GPR) is an effective geophysical electromagnetic method for underground target detection. However, the target response is usually overwhelmed by strong clutter, thus damaging the detection performance.
Li Liu +6 more
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Repositioning Drugs on Human Influenza A Viruses Based on a Novel Nuclear Norm Minimization Method [PDF]
Frontiers in Physiology, 2021 Influenza A viruses, especially H3N2 and H1N1 subtypes, are viruses that often spread among humans and cause influenza pandemic. There have been several big influenza pandemics that have caused millions of human deaths in history, and the threat of ...
Hang Liang +8 more
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Direction of Arrival Estimation for MIMO Radar via Unitary Nuclear Norm Minimization [PDF]
Sensors, 2017 In this paper, we consider the direction of arrival (DOA) estimation issue of noncircular (NC) source in multiple-input multiple-output (MIMO) radar and propose a novel unitary nuclear norm minimization (UNNM) algorithm.
Xianpeng Wang +3 more
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Low-Rank Tensor Completion by Sum of Tensor Nuclear Norm Minimization
IEEE Access, 2019 In this paper, we study the problem of low-rank tensor completion with the purpose of recovering a low-rank tensor from a tensor with partial observed items. To date, there are several different definitions of tensor ranks.
Yaru Su, Xiaohui Wu, Wenxi Liu
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Truncated enhanced constraint for low-rank plus sparse in cardiac dynamic MRI reconstruction [PDF]
Magnetic Resonance LettersCardiac dynamic MRI has been widely used in cine and perfusion imaging, in which low-rank and sparse priors play an important role in reconstructing dynamic images with high temporal and spatial resolution from undersampled acquisition.
Runyu Yang +4 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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NON-LINEAR MULTI-FRAME IMAGE DENOISING USING WEIGHTED NUCLEAR NORM MINIMIZATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 We address the problem of constructing single low noise image from a sequence of multiple noisy images. We use the approach based on finding and averaging similar blocks in the image and extend it to multiple images.
A. V. Nasonov +2 more
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BANNMDA: a computational model for predicting potential microbe–drug associations based on bilinear attention networks and nuclear norm minimization [PDF]
Frontiers in MicrobiologyLiang M +7 more
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Traffic Data Restoration Method Based on Tensor Weighting and Truncated Nuclear Norm [PDF]
Jisuanji kexue, 2023 The problem of missing data seriously affects a series of activities in intelligent transportation systems,such as monitoring traffic dynamics,predicting traffic flow,and deploying traffic planning through data.Therefore,a traffic flow data ...
WU Jiangnan, ZHANG Hongmei, ZHAO Yongmei, ZENG Hang, HU Gang
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