About this Research Topic

Background

In many application areas, it is common to collect data that are structured as a multiway array or tensor, for example, brain images, facial images, infrared images, gene expression data, social relation data, and climatology data. Tensors are often used to represent complex data sets. Traditional data analysis methods rely on representation and computation in the form of vectors and matrices, where multi-dimensional data are unfolded into a matrix for processing. However, the multilinear structure would be lost in such vectorization or matricization, which leads to sub-optimal performance in processing. It is necessary to explore novel statistical methods to analyze tensor data.

We intend to collect relevant articles and promote the development of tensor analysis, especially tensor completion, tensor decomposition algorithms, and tensor regression. Since the datasets in practice are often incomplete, much of the early research was conducted on tensor decomposition with missing values, which could be regarded as the pioneer problem of tensor completion. In recent years there has been a large amount of literature relating to tensor completion. Moreover, tensor regression frameworks are being developed to better explore the multiway dependencies along the high-dimensional input and output. Efficient statistical inference methods for tensor regression are increasingly important. The goal of this Research Topic is to further the research on tensor completion approaches, parametric estimation methods in various tensor regression methods, and novel applications for tensor analysis approaches.

Particular topics of interest, include, but are not limited to:

• Tensor completion/tensor estimation

• Tensor regression

• Tensor Network analysis

• Bayesian inference for tensor completion/tensor regression

• Variational inference for tensor data

• Image data analysis based on tensor data

• Tensor decomposition/tensor factorization

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: statistical inference, tensor, tensor completion, tensor regression, Bayesian inference, tensor decomposition, tensor factorization

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