Results 11 to 20 of about 196,468 (204)

Data mining by nonnegative tensor approximation [PDF]

2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2014
Inferring multilinear dependences within multi-way data can be performed by tensor decompositions. Because of the presence of noise or modeling errors, the problem actually requires an approximation of lower rank. We concentrate on the case of real 3-way data arrays with nonnegative values, and propose an unconstrained algorithm resorting to an ...
Cabral Farias, Rodrigo, Comon, Pierre, Redon, Roland   +2 more
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On the largest eigenvalue of a symmetric nonnegative tensor [PDF]

Numerical Linear Algebra with Applications, 2013
SUMMARYIn this paper, some important spectral characterizations of symmetric nonnegative tensors are analyzed. In particular, it is shown that a symmetric nonnegative tensor has the following properties: (i) its spectral radius is zero if and only if it is a zero tensor; (ii) it is weakly irreducible (respectively, irreducible) if and only if it has a ...
Guanglu Zhou, Liqun Qi 0001, Soon-Yi Wu
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Nonnegative Structured Kruskal Tensor Regression

2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2023
Peer ...
Ollila Esa, Vorobyov Sergiy A., Wang Xinjue   +2 more
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Nonnegative Tensor CP Decomposition of Hyperspectral Data [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2016
New hyperspectral missions will collect huge amounts of hyperspectral data. In addition, it is possible now to acquire time series and multiangular hyperspectral images. The process and analysis of these big data collections will require common hyperspectral techniques to be adapted or reformulated.
Veganzones, Miguel Angel, Cohen, Jérémy, Cabral Farias, Rodrigo, Chanussot, Jocelyn, Comon, Pierre   +4 more
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Quasi-Irreducibility of Nonnegative Biquadratic Tensors

Mathematics
While the adjacency tensor of a bipartite 2-graph is a nonnegative biquadratic tensor, it is inherently reducible. To address this limitation, we introduce the concept of quasi-irreducibility in this paper.
Liqun Qi, Chunfeng Cui, Yi Xu
doaj   +2 more sources

NONNEGATIVE TENSOR FACTORIZATION FOR CONTINUOUS EEG CLASSIFICATION

International Journal of Neural Systems, 2007
In this paper we present a method for continuous EEG classification, where we employ nonnegative tensor factorization (NTF) to determine discriminative spectral features and use the Viterbi algorithm to continuously classify multiple mental tasks. This is an extension of our previous work on the use of nonnegative matrix factorization (NMF) for EEG ...
Hyekyoung Lee, Yong-Deok Kim, Andrzej Cichocki, Seungjin Choi   +3 more
openaire   +4 more sources

Generalized nonnegative structured Kruskal tensor regression

Signal Processing
This paper introduces Generalized Nonnegative Structured Kruskal Tensor Regression (NS-KTR), a novel tensor regression framework that enhances interpretability and performance through mode-specific hybrid regularization and nonnegativity constraints.
Xinjue Wang, Esa Ollila, Sergiy A. Vorobyov, Ammar Mian   +3 more
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Strictly nonnegative tensors and nonnegative tensor partition [PDF]

Science China Mathematics, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hu, Shenglong, Huang, Zhenghai, Qi, Liqun   +2 more
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On Tensors, Sparsity, and Nonnegative Factorizations [PDF]

SIAM Journal on Matrix Analysis and Applications, 2012
Tensors have found application in a variety of fields, ranging from chemometrics to signal processing and beyond. In this paper, we consider the problem of multilinear modeling of sparse count data. Our goal is to develop a descriptive tensor factorization model of such data, along with appropriate algorithms and theory.
Eric C. Chi, Tamara G. Kolda
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A new modified Newton iteration for computing nonnegative Z-eigenpairs of nonnegative tensors [PDF]

, 2022
We propose a new modification of Newton iteration for finding some nonnegative Z-eigenpairs of a nonnegative tensor. The method has local quadratic convergence to a nonnegative eigenpair of a nonnegative tensor, under the usual assumption guaranteeing ...
Lin, Wen-Wei, Guo, Chun-Hua, Liu, Ching-Sung   +2 more
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