Tensors in statistics

X Bi, X Tang, Y Yuan, Y Zhang… - Annual review of statistics …, 2021 - annualreviews.org
This article provides an overview of tensors, their properties, and their applications in
statistics. Tensors, also known as multidimensional arrays, are generalizations of matrices to …

A contemporary and comprehensive survey on streaming tensor decomposition

K Abed-Meraim, NL Trung… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Tensor decomposition has been demonstrated to be successful in a wide range of
applications, from neuroscience and wireless communications to social networks. In an …

Tensor based temporal and multilayer community detection for studying brain dynamics during resting state fMRI

E Al-Sharoa, M Al-Khassaweneh… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Objective: In recent years, resting state fMRI has been widely utilized to understand the
functional organization of the brain for healthy and disease populations. Recent studies …

Learning to summarize Chinese radiology findings with a pre-trained encoder

Z Jiang, X Cai, L Yang, D Gao, W Zhao… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Automatic radiology report summarization has been an attractive research problem towards
computer-aided diagnosis to alleviate physicians' workload in recent years. However …

Data-driven retrieval of population-level EEG features and their role in neurodegenerative diseases

W Li, Y Varatharajah, E Dicks, L Barnard… - Brain …, 2024 - academic.oup.com
Electrophysiologic disturbances due to neurodegenerative disorders such as Alzheimer's
disease and Lewy Body disease are detectable by scalp EEG and can serve as a functional …

Temporal segmentation of EEG based on functional connectivity network structure

Z Xu, S Tang, C Liu, Q Zhang, H Gu, X Li, Z Di, Z Li - Scientific Reports, 2023 - nature.com
In the study of brain functional connectivity networks, it is assumed that a network is built
from a data window in which activity is stationary. However, brain activity is non-stationary …

Neighbor graph based tensor recovery for accurate internet anomaly detection

X Li, K **e, X Wang, G **e, K Li, J Cao… - … on Parallel and …, 2022 - ieeexplore.ieee.org
Detecting anomalous traffic is a crucial task for network management. Although many
anomaly detection algorithms have been proposed recently, constrained by their matrix …

Measuring multivariate phase synchronization with symbolization and permutation

Z Li, X Wang, Y **ng, X Zhang, T Yu, X Li - Neural Networks, 2023 - Elsevier
Phase synchronization is an important mechanism for the information processing of neurons
in the brain. Most of the current phase synchronization measures are bivariate and focus on …

Enhanced network traffic anomaly detection: Integration of tensor eigenvector centrality with low-rank recovery models

W Lin, C Li, L Xu, K **e - IEEE Transactions on Services …, 2024 - ieeexplore.ieee.org
In service computing, network traffic anomaly detection is pivotal for monitoring and
identifying irregularities in network traffic to uphold the security, reliability, and stability of …

Deriving electrophysiological brain network connectivity via tensor component analysis during freely listening to music

Y Zhu, J Liu, K Mathiak, T Ristaniemi… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Recent studies show that the dynamics of electrophysiological functional connectivity is
attracting more and more interest since it is considered as a better representation of …