Results 21 to 30 of about 130 (119)
Classification Analysis of Tensor-Based Recovered Missing EEG Data
IEEE Access, 2021 This paper discusses impact of recovering missing Electroencephalography (EEG) data on classification accuracy of hand movements using tensor-based methods.
Muhammad Akmal +2 more
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Scenario Discovery Using Nonnegative Tensor Factorization [PDF]
, 2008 In the relatively new field of visual analytics there is a great need for automated approaches to both verify and discover the intentions and schemes of primary actors through time. Data mining and knowledge discovery play critical roles in facilitating the ability to extract meaningful information from large and complex textual-based (digital ...
Brett W. Bader +2 more
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Modeling Hierarchical Seasonality Through Low-Rank Tensor Decompositions in Time Series Analysis
IEEE Access, 2023 Accurately representing periodic behavior is a frequently encountered challenge in modeling time series. This is especially true for observations where multiple, nested seasonalities are present, which is often encountered in data that pertain to ...
Melih Barsbey, Ali Taylan Cemgil
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Discriminative Nonnegative Tucker Decomposition for Tensor Data Representation
Mathematics, 2022 Nonnegative Tucker decomposition (NTD) is an unsupervised method and has been extended in many applied fields. However, NTD does not make use of the label information of sample data, even though such label information is available.
Wenjing Jing, Linzhang Lu, Qilong Liu
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iScience, 2022 Summary: Symptoms of adverse reactions to vaccines evolve over time, but traditional studies have focused only on the frequency and intensity of symptoms.
Kei Ikeda +16 more
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Model Selection for Non-Negative Tensor Factorization with Minimum Description Length
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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SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 Existing tensor factorization methods assume that the input tensor follows some specific distribution (i.e. Poisson, Bernoulli, and Gaussian), and solve the factorization by minimizing some empirical loss functions defined based on the corresponding distribution.
Ardavan Afshar +6 more
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Application of Non-Negative Tensor Factorization for Airport Flight Delay Pattern Recognition
IEEE Access, 2019 With the rapid development of civil aviation transportation in China, huge demand growth has broken the balance between supply and demand, resulting in airspace congestion and increasing flight delays.
Han Zhong +3 more
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Nonnegative tensor factorization for contaminant source identification
Journal of Contaminant Hydrology, 2019 Unsupervised Machine Learning (ML) is becoming increasingly popular for solving various types of data analytics problems including feature extraction, blind source separation, exploratory analyses, model diagnostics, etc. Here, we have developed a new unsupervised ML method based on Nonnegative Tensor Factorization (NTF) for identification of the ...
Velimir V. Vesselinov +2 more
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Mobility Mining Using Nonnegative Tensor Factorization [PDF]
, 2017 Mobility mining has lots of applications in urban planning and transportation systems. In particular, extracting mobility patterns enables service providers to have a global insight about the mobility behaviors which consequently leads to providing better services to the citizens.
Hamid Eslami Nosratabadi +2 more
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