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Local Learning Rules for Nonnegative Tucker Decomposition
2009Analysis of data with high dimensionality in modern applications, such as spectral analysis, neuroscience, chemometrices naturally requires tensorial approaches different from standard matrix factorizations (PCA, ICA, NMF). The Tucker decomposition and its constrained versions with sparsity and/or nonnegativity constraints allow for the extraction of ...
Anh Huy Phan 0001, Andrzej Cichocki
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Sparse Symmetric Format for Tucker Decomposition
IEEE Transactions on Parallel and Distributed Systems, 2023Shruti Shivakumar +3 more
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Accurate regularized Tucker decomposition for image restoration
Applied Mathematical Modelling, 2023Wenwu Gong, Zhejun Huang
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The correlation-based tucker decomposition for hyperspectral image compression
Neurocomputing, 2021Zhibin Pan
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Fast Recursive Nonnegative Standard and Hierarchical Tucker Decomposition
IEEE Signal Processing Letters, 2019Krzysztof Fonał, Rafał Zdunek
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HOID: Higher Order Interpolatory Decomposition for Tensors Based on Tucker Representation
SIAM Journal on Matrix Analysis and Applications, 2016Arvind K Saibaba
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Hyperspectral image compression based on lapped transform and Tucker decomposition
Signal Processing: Image Communication, 2015Lei Wang, Jiaji Wu, Gwanggil Jeon
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Image Representation and Learning With Graph-Laplacian Tucker Tensor Decomposition
IEEE Transactions on Cybernetics, 2019Bo Jiang, Chris Ding, Jin Tang
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