Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning
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Publication:1669074
DOI10.1016/j.neunet.2015.01.001zbMath1394.68307OpenAlexW2104144964WikidataQ41507785 ScholiaQ41507785MaRDI QIDQ1669074
Yong Peng, Suhang Wang, Bao-Liang Lu
Publication date: 30 August 2018
Published in: Neural Networks (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.neunet.2015.01.001
face recognitionlow-rank representationsemi-supervised learninggraph constructionsparse manifold adaption
Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)
Related Items (4)
Manifold adaptive kernelized low-rank representation for semisupervised image classification ⋮ Accelerated low-rank representation for subspace clustering and semi-supervised classification on large-scale data ⋮ Addressing label ambiguity imbalance in candidate labels: measures and disambiguation algorithm ⋮ Sparse subspace clustering for data with missing entries and high-rank matrix completion
Uses Software
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