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Found 4 papers, 2 papers with code
Coupled Support Tensor Machine Classification for Multimodal Neuroimaging Data
Learning from multimodal data is of great interest in machine learning and statistics research as this offers the possibility of capturing complementary information among modalities.
Low-rank on Graphs plus Temporally Smooth Sparse Decomposition for Anomaly Detection in Spatiotemporal Data
In particular, the anomaly detection problem is formulated as a robust lowrank + sparse tensor decomposition with a regularization term that minimizes the temporal variation of the sparse part, so that the extracted anomalies are temporally persistent.
GLOSS: Tensor-Based Anomaly Detection in Spatiotemporal Urban Traffic Data
Anomaly detection in spatiotemporal data is a challenging problem encountered in a variety of applications including hyperspectral imaging, video surveillance and urban traffic monitoring.
Multi-Branch Tensor Network Structure for Tensor-Train Discriminant Analysis
In this paper, we introduce a supervised learning approach for tensor classification based on the tensor-train model.
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