In recent years, the application of tensors has become more widespread in fields that involve data analytics and numerical computation. Due to explosive growth data, low-rank tensor decompositions have a powerful tool harness notorious curse dimensionality . The main forms decomposition include CP decomposition, Tucker train (TT) etc. Each existing TT algorithms, including TT-SVD randomized TT-...

The problem of detecting anomalies in time series from network measurements has been widely studied and is a topic fundamental importance. Many anomaly detection methods are based on the inspection packets collected at core routers, with consequent disadvantages terms computational cost privacy. We propose an alternative method which packet header not needed. extraction normal subspace obtained...

Tensor data with rich structural information become increasingly important in process modeling, monitoring, and diagnosis manufacturing medical other applications. Here is referred to the of tensor components such as sparsity, smoothness, low-rank, piecewise constancy. To reveal useful from data, we propose decompose into summation multiple based on their different information. In this article,...