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   Articles with "negative matrix" as a keyword



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Orthogonal incremental non-negative matrix factorization algorithm and its application in image classification

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recommendations! Published in 2020 at "Computational and Applied Mathematics"

DOI: 10.1007/s40314-020-1091-2

Abstract: To improve the sparseness of the base matrix in incremental non-negative matrix factorization, we in this paper present a new method, orthogonal incremental non-negative matrix factorization algorithm (OINMF), which combines the orthogonality constraint with incremental… read more here.

Keywords: negative matrix; matrix; incremental non; matrix factorization ... See more keywords
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A kernel non-negative matrix factorization framework for single cell clustering

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recommendations! Published in 2021 at "Applied Mathematical Modelling"

DOI: 10.1016/j.apm.2020.08.065

Abstract: Abstract The emergence of single-cell RNA-sequencing is ideally placed to unravel cellular heterogeneity in biological systems, an extremely challenging problem in single cell RNA-sequencing studies. However, most current computational approaches lack the sensitivity to reliably… read more here.

Keywords: matrix factorization; kernel non; cell; single cell ... See more keywords
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Using non-negative matrix factorisation to facilitate efficient bird species richness surveys

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recommendations! Published in 2017 at "Ecological Indicators"

DOI: 10.1016/j.ecolind.2017.05.017

Abstract: This paper considers computer-assisted learning of sound spectra in environmental recordings to facilitate manual bird species identification. Today, a variety of automated methods have been successfully applied for acoustic recognition of specific bird species. These… read more here.

Keywords: negative matrix; bird; matrix factorisation; non negative ... See more keywords
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Learning Multimorbidity Patterns from Electronic Health Records Using Non-negative Matrix Factorisation

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recommendations! Published in 2020 at "Journal of biomedical informatics"

DOI: 10.1016/j.jbi.2020.103606

Abstract: Multimorbidity, or the presence of several medical conditions in the same individual, has been increasing in the population - both in absolute and relative terms. Nevertheless, multimorbidity remains poorly understood, and the evidence from existing… read more here.

Keywords: using non; negative matrix; multimorbidity; multimorbidity patterns ... See more keywords
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Investigating microstructural variation in the human hippocampus using non-negative matrix factorization

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recommendations! Published in 2020 at "NeuroImage"

DOI: 10.1016/j.neuroimage.2019.116348

Abstract: In this work we use non-negative matrix factorization to identify patterns of microstructural variance in the human hippocampus. We utilize high-resolution structural and diffusion magnetic resonance imaging data from the Human Connectome Project to query… read more here.

Keywords: hippocampus; negative matrix; factorization; matrix factorization ... See more keywords
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Analyses of microstructural variation in the human striatum using non-negative matrix factorization

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recommendations! Published in 2022 at "NeuroImage"

DOI: 10.1016/j.neuroimage.2021.118744

Abstract: The striatum is a major subcortical connection hub that has been heavily implicated in a wide array of motor and cognitive functions. Here, we developed a normative multimodal, data-driven microstructural parcellation of the striatum using… read more here.

Keywords: matrix factorization; using non; negative matrix; striatum ... See more keywords
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Non-negative matrix factorisation is the most appropriate method for extraction of muscle synergies in walking and running

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recommendations! Published in 2020 at "Scientific Reports"

DOI: 10.1038/s41598-020-65257-w

Abstract: Muscle synergies provide a simple description of a complex motor control mechanism. Synergies are extracted from muscle activation patterns using factorisation methods. Despite the availability of several factorisation methods in the literature, the most appropriate… read more here.

Keywords: negative matrix; muscle; factorisation; matrix factorisation ... See more keywords
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Non-negative matrix factorization for overlapping community detection in directed weighted networks with sparse constraints.

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recommendations! Published in 2023 at "Chaos"

DOI: 10.1063/5.0152280

Abstract: Detecting overlapping communities is essential for analyzing the structure and function of complex networks. However, most existing approaches only consider network topology and overlook the benefits of attribute information. In this paper, we propose a… read more here.

Keywords: topology; matrix factorization; non negative; negative matrix ... See more keywords
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A novel industrial process fault monitoring method based on kernel robust non-negative matrix factorization

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recommendations! Published in 2021 at "Measurement Science and Technology"

DOI: 10.1088/1361-6501/ac0de2

Abstract: Industrial processes are characterized by large amounts of nonlinear and noisy data, which pose a critical challenge to the accuracy and rapidity of fault detection. In this paper, an industrial process fault monitoring method based… read more here.

Keywords: fault; negative matrix; matrix; matrix factorization ... See more keywords
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Application of non-negative matrix factorization in oncology: one approach for establishing precision medicine

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recommendations! Published in 2022 at "Briefings in Bioinformatics"

DOI: 10.1093/bib/bbac246

Abstract: Abstract The increase in the expectations of artificial intelligence (AI) technology has led to machine learning technology being actively used in the medical field. Non-negative matrix factorization (NMF) is a machine learning technique used for… read more here.

Keywords: oncology; precision medicine; non negative; negative matrix ... See more keywords
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Multi-project and Multi-profile joint Non-negative Matrix Factorization for cancer omic datasets.

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recommendations! Published in 2021 at "Bioinformatics"

DOI: 10.1093/bioinformatics/btab579

Abstract: MOTIVATION The integration of multi-omic data using machine learning methods has been focused on solving relevant tasks such as predicting sensitivity to a drug or subtyping patients. Recent integration methods, such as joint Non-negative Matrix… read more here.

Keywords: multi; negative matrix; joint non; matrix factorization ... See more keywords