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Multi-view data visualisation via manifold learning [PDF]
PeerJ Computer ScienceNon-linear dimensionality reduction can be performed by manifold learning approaches, such as stochastic neighbour embedding (SNE), locally linear embedding (LLE) and isometric feature mapping (ISOMAP).
Theodoulos Rodosthenous +2 more
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Robust integrative biclustering for multi-view data. [PDF]
Stat Methods Med Res, 2022 In many biomedical research, multiple views of data (e.g. genomics, proteomics) are available, and a particular interest might be the detection of sample subgroups characterized by specific groups of variables. Biclustering methods are well-suited for this problem as they assume that specific groups of variables might be relevant only to specific ...
Zhang W +4 more
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Multi-View Data Analysis Techniques for Monitoring Smart Building Systems [PDF]
Sensors, 2021 In smart buildings, many different systems work in coordination to accomplish their tasks. In this process, the sensors associated with these systems collect large amounts of data generated in a streaming fashion, which is prone to concept drift.
Vishnu Manasa Devagiri +4 more
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Data Anonymization through Collaborative Multi-view Microaggregation [PDF]
Journal of Intelligent Systems, 2020 The interest in data anonymization is exponentially growing, motivated by the will of the governments to open their data. The main challenge of data anonymization is to find a balance between data utility and the amount of disclosure risk.
Zouinina Sarah +3 more
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On the use of ensemble method for multi view textual data [PDF]
Journal of Information and Telecommunication, 2020 Nowadays, trends detection is an important task on social media to determine trends that are being discussed the most on a social platform. One of the main challenges of this task is the processing of unstructured textual data which has different ...
Maha Fraj +2 more
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IEEE Access, 2022 Clustering of multi-view data has got broad consideration of the researchers. Multi-view data is composed through different domain which shows the consistent and complementary behavior.
Mohammad Ahmar Khan +8 more
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Axioms, 2023 The generation of unprecedented amounts of data brings new challenges in data management, but also an opportunity to accelerate the identification of processes of multiple science disciplines.
Deniz Akdemir +2 more
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Multi-view kernel consensus for data analysis [PDF]
Applied and Computational Harmonic Analysis, 2020 The input data features set for many data driven tasks is high-dimensional while the intrinsic dimension of the data is low. Data analysis methods aim to uncover the underlying low dimensional structure imposed by the low dimensional hidden parameters by utilizing distance metrics that consider the set of attributes as a single monolithic set. However,
Salhov, Moshe +5 more
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A multi-view genomic data simulator [PDF]
BMC Bioinformatics, 2015 OMICs technologies allow to assay the state of a large number of different features (e.g., mRNA expression, miRNA expression, copy number variation, DNA methylation, etc.) from the same samples. The objective of these experiments is usually to find a reduced set of significant features, which can be used to differentiate the conditions assayed.
Michele Fratello +5 more
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Joint association and classification analysis of multi‐view data [PDF]
Biometrics, 2021 AbstractMulti‐view data, which is matched sets of measurements on the same subjects, have become increasingly common with advances in multi‐omics technology. Often, it is of interest to find associations between the views that are related to the intrinsic class memberships.
Yunfeng Zhang, Irina Gaynanova
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