Tensor-on-tensor regression
EF Lock - Journal of Computational and Graphical Statistics, 2018 - Taylor & Francis
ABSTRACT I propose a framework for the linear prediction of a multiway array (ie, a tensor)
from another multiway array of arbitrary dimension, using the contracted tensor product. This …
from another multiway array of arbitrary dimension, using the contracted tensor product. This …
Uncorrelated multilinear discriminant analysis with regularization and aggregation for tensor object recognition
H Lu, KN Plataniotis… - IEEE Transactions on …, 2008 - ieeexplore.ieee.org
This paper proposes an uncorrelated multilinear discriminant analysis (UMLDA) framework
for the recognition of multidimensional objects, known as tensor objects. Uncorrelated …
for the recognition of multidimensional objects, known as tensor objects. Uncorrelated …
[PDF][PDF] 具有模糊聚类功能的双向二维无监督特征提取方法
皋军， 孙长银， 王士同 - 自动化学报, 2012 - aas.net.cn
摘要依据最大间距判别准则(Maximum margin criterion, MMC) 的基本原理,
并结合模糊技术和张量理论, 提出一种矩阵模式的模糊最大间距判别准则(Matrix model fuzzy …
并结合模糊技术和张量理论, 提出一种矩阵模式的模糊最大间距判别准则(Matrix model fuzzy …
[PDF][PDF] A taxonomy of emerging multilinear discriminant analysis solutions for biometric signal recognition
H Lu, KN Plataniotis… - … : Theory, Methods, and …, 2009 - academia.edu
Many biometric signals, such as fingerprint, palmprint, ear, face images, and gait silhouettes
sequences, are naturally multidimensional objects, which are formally referred to as tensor …
sequences, are naturally multidimensional objects, which are formally referred to as tensor …
Feature fusion using multiple component analysis
S Hou, Q Sun, D Xia - Neural processing letters, 2011 - Springer
Canonical correlation analysis (CCA) and partial least squares (PLS) are always used as
fusing two feature sets. How to extend them to fuse multiple features in a generalized way is …
fusing two feature sets. How to extend them to fuse multiple features in a generalized way is …
[图书][B] Multilinear subspace learning for face and gait recognition
H Lu - 2008 - library-archives.canada.ca
Face and gait recognition problems are challenging due to largely varying appearances,
highly complex pattern distributions, and insufficient training samples. This dissertation …
highly complex pattern distributions, and insufficient training samples. This dissertation …
Ranking tensor subspaces in weighted multilinear principal component analysis
Multilinear principal component analysis (MPCA) has been applied for tensor decomposition
and dimensionality reduction in image databases modeled through higher order tensors …
and dimensionality reduction in image databases modeled through higher order tensors …
Color-based feature extraction with application to facial recognition using tensor-matrix and tensor-tensor analysis
In this article, two main goals are investigated. 1) Developing the capabilities of tensor
analysis into machine learning and pattern recognition applications such as facial …
analysis into machine learning and pattern recognition applications such as facial …
Comparing ranking methods for tensor components in multilinear and concurrent subspace analysis with applications in face images
In the area of multi-dimensional image databases modeling, the multilinear principal
component analysis (MPCA) and concurrent subspace analysis (CSA) approaches were …
component analysis (MPCA) and concurrent subspace analysis (CSA) approaches were …
Face recognition using new image representations
Z Liu, Q Tao - 2009 International Joint Conference on Neural …, 2009 - ieeexplore.ieee.org
This paper presents a novel face recognition method by using the new image
representations. While the commonly used gray-scale image is derived from the linear …
representations. While the commonly used gray-scale image is derived from the linear …