Results 11 to 20 of about 1,665,186 (233)
Fast Circulant Tensor Power Method for High-Order Principal Component Analysis
IEEE Access, 2021 To understand high-order intrinsic key patterns in high-dimensional data, tensor decomposition is a more versatile tool for data analysis than standard flat-view matrix models. Several existing tensor models aim to achieve rapid computation of high-order
Taehyeon Kim, Yoonsik Choe
doaj +1 more source
DeepTensor: Low-Rank Tensor Decomposition With Deep Network Priors [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 DeepTensor is a computationally efficient framework for low-rank decomposition of matrices and tensors using deep generative networks. We decompose a tensor as the product of low-rank tensor factors (e.g., a matrix as the outer product of two vectors ...
Vishwanath Saragadam +3 more
semanticscholar +1 more source
Block Row Kronecker-Structured Linear Systems With a Low-Rank Tensor Solution
Frontiers in Applied Mathematics and Statistics, 2022 Several problems in compressed sensing and randomized tensor decomposition can be formulated as a structured linear system with a constrained tensor as the solution.
Stijn Hendrikx +3 more
doaj +1 more source
Searching to Sparsify Tensor Decomposition for N-ary Relational Data [PDF]
The Web Conference, 2021 Tensor, an extension of the vector and matrix to the multi-dimensional case, is a natural way to describe the N-ary relational data. Recently, tensor decomposition methods have been introduced into N-ary relational data and become state-of-the-art on ...
Shimin Di, Quanming Yao, Lei Chen
semanticscholar +1 more source
N Dimensional Tensor Decomposition Recommendation Algorithm Based on User’s Neighbors [PDF]
Jisuanji gongcheng, 2017 Recommendation algorithm based on tensor factorization has low accuracy and data sparseness problem.Therefore,on the basic of the traditional tensor decomposition model,this paper introduces the user nearest neighbor information,and proposes N ...
CHEN Jianmei,SUN Yajun
doaj +1 more source
A Contemporary and Comprehensive Survey on Streaming Tensor Decomposition
IEEE Transactions on Knowledge and Data Engineering, 2023 Tensor decomposition has been demonstrated to be successful in a wide range of applications, from neuroscience and wireless communications to social networks. In an online setting, factorizing tensors derived from multidimensional data streams is however
Thanh Trung LE +3 more
semanticscholar +1 more source
DOA Estimation for Transmit Beamspace MIMO Radar via Tensor Decomposition With Vandermonde Factor Matrix [PDF]
IEEE Transactions on Signal Processing, 2021 We address the problem of tensor decomposition in application to direction-of-arrival (DOA) estimation for two-dimensional transmit beamspace (TB) multiple-input multiple-output (MIMO) radar.
Feng Xu, M. Morency, S. Vorobyov
semanticscholar +1 more source
Tensor Decomposition-Inspired Convolutional Autoencoders for Hyperspectral Anomaly Detection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Anomaly detection from hyperspectral images (HSI) is an important task in the remote sensing domain. Considering the three-order characteristics of HSI, many tensor decomposition based hyperspectral anomaly detection (HAD) models have been proposed and ...
Bangyong Sun +4 more
doaj +1 more source
Skew-symmetric tensor decomposition [PDF]
Communications in Contemporary Mathematics, 2019 We introduce the “skew apolarity lemma” and we use it to give algorithms for the skew-symmetric rank and the decompositions of tensors in [Formula: see text] with [Formula: see text] and [Formula: see text]. New algorithms to compute the rank and a minimal decomposition of a tritensor are also presented.
Enrique Esteban Arrondo +3 more
openaire +5 more sources
EA-ADMM: noisy tensor PARAFAC decomposition based on element-wise average ADMM
EURASIP Journal on Advances in Signal Processing, 2022 Tensor decomposition is widely used to exploit the internal correlation in multi-way data analysis and process for communications and radar systems.
Gang Yue, Zhuo Sun
doaj +1 more source