Results 21 to 30 of about 2,754 (231)

Tensor Ring Decomposition

, 2016
Tensor networks have in recent years emerged as the powerful tools for solving the large-scale optimization problems. One of the most popular tensor network is tensor train (TT) decomposition that acts as the building blocks for the complicated tensor networks.
Zhao, Qibin, Zhou, Guoxu, Xie, Shengli, Zhang, Liqing, Cichocki, Andrzej   +4 more
openaire   +2 more sources

Block-Randomized Stochastic Methods for Tensor Ring Decomposition

, 2023
Tensor ring (TR) decomposition is a simple but effective tensor network for analyzing and interpreting latent patterns of tensors. In this work, we propose a doubly randomized optimization framework for computing TR decomposition. It can be regarded as a sensible mix of randomized block coordinate descent and stochastic gradient descent, and hence ...
Yu, Yajie, Li, Hanyu, Zhou, Jingchun
openaire   +2 more sources

Tracking tensor ring decompositions of streaming tensors

Computational and Applied Mathematics
Tensor ring (TR) decomposition is an efficient approach to discover the hidden low-rank patterns for higher-order tensors, and streaming tensors are becoming highly prevalent in real-world applications. In this paper, we investigate how to track TR decompositions of streaming tensors. An efficient algorithm is first proposed.
Yajie Yu, Hanyu Li
openaire   +2 more sources

Practical sketching‐based randomized tensor ring decomposition

Numerical Linear Algebra with Applications
AbstractBased on sketching techniques, we propose two practical randomized algorithms for tensor ring (TR) decomposition. Specifically, on the basis of defining new tensor products and investigating their properties, the two algorithms are devised by applying the Kronecker sub‐sampled randomized Fourier transform and TensorSketch to the alternating ...
Yajie Yu, Hanyu Li
openaire   +3 more sources

Low-rank reduced biquaternion tensor ring decomposition and tensor completion

Applied Mathematics and Computation
We define the reduced biquaternion tensor ring (RBTR) decomposition and provide a detailed exposition of the corresponding algorithm RBTR-SVD. Leveraging RBTR decomposition, we propose a novel low-rank tensor completion algorithm RBTR-TV integrating RBTR ranks with total variation (TV) regularization to optimize the process.
Hui Luo, Xin Liu, Wei Liu, Yang Zhang
openaire   +2 more sources

A Bayesian Robust Tensor Ring Decomposition Model with Gaussian-Wishart Prior for Missing Traffic Data Completion

Promet (Zagreb)
The rapid development of Intelligent Transportation Systems (ITS) is often hindered by missing data due to technical or equipment failures, impacting data analysis and application.
Longsheng HUANG, Yu ZHU, Hanzeng SHAO, Yun ZHU, Gaohang YU, Jun WANG   +5 more
doaj   +1 more source

Rank minimization on tensor ring: an efficient approach for tensor decomposition and completion [PDF]

Machine Learning, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Longhao Yuan, Chao Li, Jianting Cao, Qibin Zhao   +3 more
openaire   +1 more source

Spectral Quadratic Variation Regularized Autoweighted Tensor Ring Decomposition for Hyperspectral Image Reconstruction

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
The structure information of hyperspectral image (HSI) is well-characterized by tensors, surpassing the capabilities of traditional compressive sensing reconstruction models based on vectors and matrices.
Xinwei Wan, Dan Li, Fanqiang Kong, Yanyan Lv, Qiang Wang   +4 more
doaj   +1 more source

Enhancing Low‐Temperature Performance of Sodium‐Ion Batteries via Anion‐Solvent Interactions

Advanced Functional Materials, EarlyView.
DOL is introduced into electrolytes as a co‐solvent, increasing slat solubility, ion conductivity, and the de‐solvent process, and forming an anion‐rich solvent shell due to its high interaction with anion. With the above virtues, the batteries using this electrolyte exhibit excellent cycling stability at low temperatures. Abstract Sodium‐ion batteries
Cheng Zheng, Qian Yao, Yanan Sun, Hongyu Lv, Zhongchao Bai, Guoliang Zhang, Nana Wang, Jian Yang   +7 more
wiley   +1 more source

A Sampling-Based Method for Tensor Ring Decomposition

, 2020
We propose a sampling-based method for computing the tensor ring (TR) decomposition of a data tensor. The method uses leverage score sampled alternating least squares to fit the TR cores in an iterative fashion. By taking advantage of the special structure of TR tensors, we can efficiently estimate the leverage scores and attain a method which has ...
Malik, Osman Asif, Becker, Stephen
openaire   +2 more sources