Results 21 to 30 of about 63,767 (263)
Correction: Smartphone dependence classification using tensor factorization. [PDF]
PLoS ONE, 2017 [This corrects the article DOI: 10.1371/journal.pone.0177629.].
PLOS ONE Staff
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Predicting clinically promising therapeutic hypotheses using tensor factorization [PDF]
BMC Bioinformatics, 2019 Background Determining which target to pursue is a challenging and error-prone first step in developing a therapeutic treatment for a disease, where missteps are potentially very costly given the long-time frames and high expenses of drug development ...
Jin Yao +3 more
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Federated Tensor Factorization for Computational Phenotyping [PDF]
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2017 Tensor factorization models offer an effective approach to convert massive electronic health records into meaningful clinical concepts (phenotypes) for data analysis. These models need a large amount of diverse samples to avoid population bias. An open challenge is how to derive phenotypes jointly across multiple hospitals, in which direct patient ...
Kim, Yejin +3 more
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Discriminative and Distinct Phenotyping by Constrained Tensor Factorization [PDF]
Scientific Reports, 2017 Adoption of Electronic Health Record (EHR) systems has led to collection of massive healthcare data, which creates oppor- tunities and challenges to study them.
Yejin Kim +4 more
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Navigating the Functional Landscape of Transcription Factors via Non-Negative Tensor Factorization Analysis of MEDLINE Abstracts [PDF]
Frontiers in Bioengineering and Biotechnology, 2017 In this study, we developed and evaluated a novel text-mining approach, using non-negative tensor factorization (NTF), to simultaneously extract and functionally annotate transcriptional modules consisting of sets of genes, transcription factors (TFs ...
Sujoy Roy +9 more
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Spatial Low-Rank Tensor Factorization and Unmixing of Hyperspectral Images
Computers, 2021 This work presents a method for hyperspectral image unmixing based on non-negative tensor factorization. While traditional approaches may process spectral information without regard for spatial structures in the dataset, tensor factorization preserves ...
William Navas-Auger, Vidya Manian
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Sparse and Low-Rank Constrained Tensor Factorization for Hyperspectral Image Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Third-order tensors have been widely used in hyperspectral remote sensing because of their ability to maintain the 3-D structure of hyperspectral images.
Pan Zheng, Hongjun Su, Qian Du
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Tensor factorization via transformed tensor-tensor product for image alignment
Numerical Algorithms, 2023 In this paper, we study the problem of a batch of linearly correlated image alignment, where the observed images are deformed by some unknown domain transformations, and corrupted by additive Gaussian noise and sparse noise simultaneously. By stacking these images as the frontal slices of a third-order tensor, we propose to utilize the tensor ...
Xia, Sijia, Qiu, Duo, Zhang, Xiongjun
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Frontiers in Earth Science, 2023 Restoration of hyperspectral images (HSI) is a crucial step in many potential applications as a preprocessing step. Recently, low-rank tensor ring factorization was applied for HSI reconstruction, which has high-order tensors’ powerful and generalized ...
Xuegang Luo +5 more
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Decoupling braided tensor factors [PDF]
Physics of Atomic Nuclei, 2001 We briefly report on our result that the braided tensor product algebra of two module algebras $A_1,A_2$ of a quasitriangular Hopf algebra $H$ is equal to the ordinary tensor product algebra of $H_1$ with a subalgebra isomorphic to $A_2$ and commuting with $A_1$, provided there exists a realization of $H$ within $A_1$. As applications of the theorem we
FIORE, GAETANO, H. STEINHACKER, J. WESS
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