Results 1 to 10 of about 13,782,934 (217)
Sparse Non-Negative Tensor Factorization Using Columnwise Coordinate Descent [PDF]
Pattern Recognition, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Peter Wonka
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Sparse Image Coding Using a 3D Non-Negative Tensor Factorization [PDF]
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005 We introduce an algorithm for a non-negative 3D tensor factorization for the purpose of establishing a local parts feature decomposition from an object class of images. In the past, such a decomposition was obtained using non-negative matrix factorization (NMF) where images were vectorized before being factored by NMF.
A Shashua
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Non-Negative Tensor Factorization for Human Behavioral Pattern Mining in Online Games [PDF]
Information, 2018 Multiplayer online battle arena is a genre of online games that has become extremely popular. Due to their success, these games also drew the attention of our research community, because they provide a wealth of information about human online ...
Anna Sapienza +2 more
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Model Selection for Non-Negative Tensor Factorization with Minimum Description Length [PDF]
Entropy, 2019 Non-negative tensor factorization (NTF) is a widely used multi-way analysis approach that factorizes a high-order non-negative data tensor into several non-negative factor matrices.
Yunhui Fu +2 more
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Computing Non-Negative Tensor Factorizations [PDF]
Optimization Methods and Software, 2008 Non-negative tensor factorization (NTF) is a technique for computing a parts-based representation of high-dimensional data. NTF excels at exposing latent structures in datasets, and at finding good low-rank approximations to the data. We describe an approach for computing the NTF of a dataset that relies only on iterative linear-algebra techniques and ...
Michael P. Friedlander
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Non-Negative Multiple Tensor Factorization [PDF]
2013 IEEE 13th International Conference on Data Mining, 2013 Non-negative Tensor Factorization (NTF) is a widely used technique for decomposing a non-negative value tensor into sparse and reasonably interpretable factors. However, NTF performs poorly when the tensor is extremely sparse, which is often the case with real-world data and higher-order tensors.
Hiroshi Sawada +2 more
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Non-negative tensor factorization workflow for time series biomedical data
STAR Protocols, 2023 Summary: Non-negative tensor factorization (NTF) enables the extraction of a small number of latent components from high-dimensional biomedical data. However, NTF requires many steps, which is a hurdle to implementation.
Koki Tsuyuzaki +4 more
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Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data [PDF]
Lecture Notes in Computer Science, 2015 ECML PKDD ...
Lawrence Carin +2 more
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Applied Sciences, 2019 The incipient damages of mechanical equipment excite weak impulse vibration, which is hidden, almost unobservable, in the collected signal, making fault detection and failure prevention at the inchoate stage rather challenging.
Lin Liang +4 more
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Non-Negative Tensor Factorization Models for Bayesian Audio Processing
Digital Signal Processing, 2015 We provide an overview of matrix and tensor factorization methods from a Bayesian perspective, giving emphasis on both the inference methods and modeling techniques. Factorization based models and their many extensions such as tensor factorizations have proved useful in a broad range of applications, supporting a practical and computationally tractable
Tuomas Virtanen +2 more
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