Browse State-of-the-Art › Multiview Learning
Multiview Learning
17 papers with code · 0 benchmarks · 4 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
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Libraries
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Datasets archive 2025-07-28
4 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
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Most implemented papers archive 2025-07-28
17 shown of 17 papers with code (41 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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2 Oct 2023 2 repositories listed Syntology ran 6 of 9 samples · 3 unverified · 4 pointer-only (licence)The Canonical Correlation Analysis (CCA) family of methods is foundational in multiview learning.
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17 Aug 2018 2 repositories listedDifferent experiments on three publicly available datasets show the efficiency of the proposed approach with respect to state-of-art models.
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4 Feb 2025 1 repository listedThe HCN derives three consensus indices for capturing the hierarchical consensus across views, which are classifying consensus, coding consensus, and global consensus, respectively.
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4 Aug 2024 1 repository listedIn view of the aforementioned challenges, we propose multiview twin parametric margin support vector machine (MvTPMSVM).
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2 Jun 2024 1 repository listedIt is increasingly common in a wide variety of applied settings to collect data of multiple different types on the same set of samples.
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25 Nov 2023 1 repository listedFor users with limited programming language, we provide a Shiny Application to facilitate data integration anywhere and on any device.
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22 Aug 2023 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)To facilitate the data efficiency of multiview learning, we further perform video-text alignment for first-person and third-person videos, to fully leverage the semantic knowledge to improve video representations.
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28 Feb 2023 1 repository listedAppendicitis is among the most frequent reasons for pediatric abdominal surgeries.
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15 Feb 2023 1 repository listedWe propose iDeepViewLearn (Interpretable Deep Learning Method for Multiview Learning) for learning nonlinear relationships in data from multiple views while achieving feature selection.
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12 Apr 2022 1 repository listed Syntology ran 3 of 7 samples · 4 unverifiedTo overcome such limitations, in this paper, we propose a methodological approach for multi-view breast cancer classification based on parameterized hypercomplex neural networks.
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2 Dec 2021 1 repository listedMeanwhile, instead of using auto-encoder in most unsupervised learning graph neural networks, SDSNE uses a co-supervised strategy with structure information to supervise the model learning.
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14 Jun 2021 1 repository listed Syntology ran 0 of 3 samples · 3 unverifiedUnder this model, latent correlation maximization is shown to guarantee the extraction of the shared components across views (up to certain ambiguities).
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24 Oct 2018 1 repository listedFor representation, we consider representations based on the context distribution of the entity (i.
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25 May 2018 1 repository listedWe tackle the issue of classifier combinations when observations have multiple views.
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17 Apr 2018 1 repository listedIn addition to various spatial fusion-based methods, an affinity fusion-based network is also proposed in which the self-expressive layer corresponding to different modalities is enforced to be the same.
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6 Mar 2018 1 repository listedTo address this problem and inspired by recent works in adversarial learning, we propose a multiple kernel clustering method with the min-max framework that aims to be robust to such adversarial perturbation.
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1 Dec 2014 1 repository listedIn many modern applications from, for example, bioinformatics and computer vision, samples have multiple feature representations coming from different data sources.
Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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