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   Articles with "tensor factorization" as a keyword



Tensor Factorization for Precision Medicine in Heart Failure with Preserved Ejection Fraction

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recommendations! Published in 2017 at "Journal of Cardiovascular Translational Research"

DOI: 10.1007/s12265-016-9727-8

Abstract: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous clinical syndrome that may benefit from improved subtyping in order to better characterize its pathophysiology and to develop novel targeted therapies. The United States Precision… read more here.

Keywords: medicine; precision medicine; heart failure; tensor factorization ... See more keywords

Nonnegative tensor factorization for contaminant source identification.

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recommendations! Published in 2019 at "Journal of contaminant hydrology"

DOI: 10.1016/j.jconhyd.2018.11.010

Abstract: Unsupervised Machine Learning (ML) is becoming increasingly popular for solving various types of data analytics problems including feature extraction, blind source separation, exploratory analyses, model diagnostics, etc. Here, we have developed a new unsupervised ML… read more here.

Keywords: methodology; tensor factorization; groundwater types; contaminant ... See more keywords
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Non-recurrent Traffic Congestion Detection with a Coupled Scalable Bayesian Robust Tensor Factorization Model

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recommendations! Published in 2021 at "Neurocomputing"

DOI: 10.1016/j.neucom.2020.10.091

Abstract: Non-recurrent traffic congestion (NRTC) usually brings unexpected delays to commuters. Hence, it is critical to accurately detect and recognize the NRTC in a real-time manner. The advancement of road traffic detectors and loop detectors provides… read more here.

Keywords: traffic; framework; tensor; bayesian robust ... See more keywords
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FedPAR: Federated PARAFAC2 tensor factorization for computational phenotyping

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recommendations! Published in 2024 at "IISE Transactions on Healthcare Systems Engineering"

DOI: 10.1080/24725579.2024.2333261

Abstract: Abstract Modeling temporally irregular electronic health records (EHRs) through computational phenotyping that transforms massive EHR data into clinically meaningful medical concepts has become critical in the healthcare industry. PARAFAC2 tensor factorization has demonstrated effectiveness in… read more here.

Keywords: parafac2; factorization; tensor factorization; parafac2 tensor ... See more keywords

Viral quasispecies reconstruction via tensor factorization with successive read removal

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recommendations! Published in 2018 at "Bioinformatics"

DOI: 10.1093/bioinformatics/bty291

Abstract: Motivation As RNA viruses mutate and adapt to environmental changes, often developing resistance to anti‐viral vaccines and drugs, they form an ensemble of viral strains‐‐a viral quasispecies. While high‐throughput sequencing (HTS) has enabled in‐depth studies… read more here.

Keywords: tensor factorization; quasispecies reconstruction; viral quasispecies;

Shape-Adaptive Tensor Factorization Model for Dimensionality Reduction of Hyperspectral Images

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recommendations! Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2935496

Abstract: Tensor-based dimensionality reduction (DR) of hyperspectral images is a promising research topic. However, patch-based tensorization usually adopts a squared neighborhood with fixed window size, which may be inaccurate in modeling the local spatial information in… read more here.

Keywords: shape adaptive; tensor; hyperspectral images; dimensionality reduction ... See more keywords

Adaptive Hypergraph Regularized Multilayer Sparse Tensor Factorization for Hyperspectral Unmixing

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recommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2023.3241115

Abstract: Hyperspectral unmixing with tensor models has received great attention in recent years. A tensor-based decomposition method can effectively represent the structural feature of hyperspectral images; however, the obtained results may be physically uninterpretable. To overcome… read more here.

Keywords: tensor factorization; tensor; adaptive hypergraph; hyperspectral unmixing ... See more keywords

Urban Trajectory Analytics: Day-of-Week Movement Pattern Mining Using Tensor Factorization

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recommendations! Published in 2019 at "IEEE Transactions on Intelligent Transportation Systems"

DOI: 10.1109/tits.2018.2868122

Abstract: This paper demonstrates the use of non-negative tensor factorization to extract underlying spatio-temporal movement patterns from large-scale urban trajectory data. Individual trajectory data obtained from public transport smart card systems and roadside Bluetooth detectors are… read more here.

Keywords: day week; day; week; tensor factorization ... See more keywords
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Coupled Graphs and Tensor Factorization for Recommender Systems and Community Detection

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recommendations! Published in 2021 at "IEEE Transactions on Knowledge and Data Engineering"

DOI: 10.1109/tkde.2019.2941716

Abstract: Joint analysis of data from multiple information repositories facilitates uncovering the underlying structure in heterogeneous datasets. Single and coupled matrix-tensor factorization (CMTF) has been widely used in this context for imputation-based recommendation from ratings, social… read more here.

Keywords: tensor; factorization; community detection; tensor factorization ... See more keywords

Complex Tensor Factorization With PARAFAC2 for the Estimation of Brain Connectivity From the EEG

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recommendations! Published in 2019 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"

DOI: 10.1109/tnsre.2018.2883514

Abstract: The coupling between neuronal populations and its magnitude have been shown to be informative for various clinical applications. One method to estimate functional brain connectivity is with electroencephalography (EEG) from which the cross spectrum between… read more here.

Keywords: brain connectivity; eeg; connectivity; tensor factorization ... See more keywords

Learning Schema Embeddings for Service Link Prediction: A Coupled Matrix-Tensor Factorization Approach

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recommendations! Published in 2025 at "IEEE Transactions on Services Computing"

DOI: 10.1109/tsc.2025.3541552

Abstract: Schema information is increasingly crucial to improve service discovery, recommendation, and composition, addressing link sparsity and lack of explainability inherent in methods relying solely on triples. However, existing approaches predominantly utilize schema information as a… read more here.

Keywords: tensor factorization; coupled matrix; service; service link ... See more keywords