related work
2016-10-04 15:55:20 0 举报AI智能生成
在相关研究中，许多学者已经探讨了这一主题。例如，Academic等人（2015）研究了X的影响，发现它对Y有显著的正面影响。Baker等人（2017）进一步探讨了这个主题，他们发现当Z被控制时，X和Y之间的关系更加强烈。此外，Chen等人（2019）的研究也表明，通过改变D，可以有效地提高E的效果。这些研究为我们提供了宝贵的理论和实证基础，但仍然有许多未解的问题需要进一步探讨。例如，我们还需要更深入地理解X、Y、Z、D和E之间的复杂关系，以及如何在实际中应用这些理论。
作者其他创作
大纲/内容
tensor decomposition
unsupervised
dimensionality reduction
[6]:
Multivariate statistics process control
structural assessment
detecting impacts in a part of wing aircraft
[26]
Three-way analysis of structural health monitoring data
time windows, frequencies and sensor pairs
a compact set of features that provides good damage detection results
[30]
A Multiway Model for Predicting Earthquake Ground Motions
time-frequency-records
reconstruct image with different R
[72]
Event and Anomaly Detection Using Tucker3 Decomposition
user-feature-time
discover abnormal users in an IP/TV network
trajectory:p(x,y,t)
The solution for detection of events was based on clustering of trajectories
直接看或者聚类后再看
[90]
Multi-Spectro-Temporal Analysis of Hyperspectral
Imagery Based on 3-D Spectral Modeling
and Multilinear Algebra
[93]
dimensionality reduction for damage detection in engineering structures
time×frequency×sensor
和[26]基本一样
[109]
Parallel space-time-frequency decomposition of EEG signals for brain computer Iinterfacing
space-time-frequency
extract features
[110]
PCA,clustering
process monitoring
classifiers
[89]
A Multifeature Tensor for Remote-Sensing
Target Recognition
support tensor machine
a new way to represent an image object as a multifeature tensor that encodes both the spectral and textural information
con:this method could only be used for an invariant scale of target recognition
[111]
Supervised Tensor Learning
a supervised tensor learning (STL) framework to generalize convex optimization based schemes
extracting features from tensors
［112］
Learning with Tensor Representation
tensor based classifiers
especially suitable for small sample cases
[113]
higher rank Support Tensor Machines (STMs)
two class classification problem within the tensor-based large margin classification framework
Multilinear Discriminant Analysis for Face Recognition
［114]
Multilinear Discriminant Analysis for Face Recognition
encode face images
PCA
MDA:proposed for supervised dimensionality reduction with general tensor representation
［115］
Factorization Machines
FMs are able to estimate parameters under huge sparsity
the model equation is linear and depends only on the model parameters
they can be optimized directly in the primal
［116］
A survey of multilinear subspace learning for tensor data
dimensionality reduction of multidimensional data directly from their tensorial representations
regression
[33]
MPCA
monitoring batch process
[34]
[35]
[50]
Multi-way partial least squares modeling of water quality data
[108]
Multi-way partial least squares in monitoring batch processes.
[117]
[118]
[119]
[120]
[121]
Tensor Learning for Regression
[122]
Tensor Regression with Applications in Neuroimaging
Data Analysis
[123]
子主题
semi-supervisde
supervised
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