Results 91 to 100 of about 130 (119)
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Nonnegative contraction/averaging tensor factorization
10th Symposium on Neural Network Applications in Electrical Engineering, 2010Nonnegative tensor factorization (NTF) is a recent multiway (multilinear) extension of negative matrix factorization (NMF), where nonnegativity constraints are mainly imposed on CANDECOMP/PARAFAC model and recently, also, on Tucker model. Nonnegative tensor factorization algorithms have many potential applications, including multiway clustering, multi ...
Marko V. Jankovic, Branimir Reljin
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Multiplicative Algorithms for Symmetric Nonnegative Tensor Factorizations and Its Applications
Journal of Scientific Computing, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Maolin Che, Yimin Wei 0001
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Nonnegative Tensor Factorization for Source Separation of Loops in Audio
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018The prevalence of exact repetition in loop-based music makes it an opportune target for source separation. Nonnegative factorization approaches have been used to model the repetition of looped content, and kernel additive modeling has leveraged periodicity within a piece to separate looped background elements.
Jordan B. L. Smith, Masataka Goto
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Algorithms for Nonnegative Tensor Factorization
2009Nonnegative Matrix Factorization (NMF) is a decomposition which incorporates nonnegativity constraints in both the weights and the bases of the representation. The nonnegativity constraints in NMF correspond better to the intuitive notion of combining parts in order to create a complete object, since the object is represented using only additions of ...
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Superpixel-Based Nonnegative Tensor Factorization for Hyperspectral Unmixing
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018Hyperspectral unmixing aims at decomposing a hyperspectral image (HSI) into a number of constituted materials and associated proportions. Recently, nonnegative tensor factorization (NTF) based methods have been proved effective and natural for hyperspectral unmixing owing to their virtue of representing an HSI without any information loss.
Fengchao Xiong +3 more
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Nonnegative Shifted Tensor Factorization in time frequency domain
2014 International Joint Conference on Neural Networks (IJCNN), 2014In this paper, we proposed a Nonnegative Shifted Tensor Factorization (NSTF) model considering multiple component delays by time frequency analysis. Explicit mathematical representation for the delays is presented to recover the patterns from the original data.
Qiang Wu 0009 +4 more
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A Projected Gradient Method for Sparse Nonnegative Tensor Factorization
2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2019Recently, nonnegative tensor factorization (NTF) has attracted much attention in many applications such as image processing, signal processing, and data mining. Since many data sets are not only nonnegative but also sparse in practical application, we detail solutions to handle a nonnegative three-way tensor with sparse and nonnegative constraints.
Liqiao Yang +2 more
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Novel hierarchical ALS algorithm for nonnegative tensor factorization
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011The multiplicative algorithms are well-known for nonnegative matrix and tensor factorizations. The ALS algorithm for canonical decomposition (CP) has been proved as a “workhorse” algorithm for general multiway data. Unfortunately, for CP with nonnegativity constraints, this algorithm with a rectifier (projection) may not converge to the desired ...
Anh Huy Phan 0001 +3 more
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Optical Engineering, 2018
Tensor display is an option in glasses-free three-dimensional (3-D) display technology. An initial solution has to be set to decompose the light-field information to be represented by the system. We have analyzed the impact of the initial guess on the multiplicative update rules in terms of peak signal-to-noise ratio, and proposed a method based on ...
David Carmona-Ballester +4 more
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Tensor display is an option in glasses-free three-dimensional (3-D) display technology. An initial solution has to be set to decompose the light-field information to be represented by the system. We have analyzed the impact of the initial guess on the multiplicative update rules in terms of peak signal-to-noise ratio, and proposed a method based on ...
David Carmona-Ballester +4 more
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Fast multiplicative algorithms for symmetric nonnegative tensor factorization
Neurocomputing, 2022Peitao Wang +5 more
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