3 citations · 6 across the 11 of their papers we have counts for
11 papers
Intrinsic Low-Tucker-Rank Theory and Unified Tensor CUR Decomposition for High-Dimensional Hyperinterpolation
Maolin Che, Yimin Wei, Chong Wu
High-dimensional hyperinterpolation is severely hampered by the curse of dimensionality, as its coefficient tensors grow exponentially with the ambient dimension. Existing research…
How many integrals should be evaluated at least in two-dimensional hyperinterpolation?
Maolin Che, Congpei An, Yimin Wei +1
This paper introduces a novel approach to approximating continuous functions over high-dimensional hypercubes by integrating matrix CUR decomposition with hyperinterpolation techni…
sparseGeoHOPCA: A Geometric Solution to Sparse Higher-Order PCA Without Covariance Estimation
Renjie Xu, Chong Wu, Maolin Che +3
We propose sparseGeoHOPCA, a novel framework for sparse higher-order principal component analysis (SHOPCA) that introduces a geometric perspective to high-dimensional tensor decomp…
Efficient randomized algorithms for the fixed Tucker-rank problem of Tucker decomposition with adaptive shifts
Maolin Che, Yimin Wei, Chong Wu +1
Randomized numerical linear algebra is proved to bridge theoretical advancements to offer scalable solutions for approximating tensor decomposition. This paper introduces fast rand…
Effective algorithms for tensor train decomposition via the UTV framework
Yuchao Wang, Maolin Che, Yimin Wei
The tensor-train (TT) decomposition is widely used to compress large tensors into a more compact form by exploiting their inherent data structures. A fundamental approach for const…
Randomized algorithms for computing the tensor train approximation and their applications
Maolin Che, Yimin Wei, Hong Yan
In this paper, we focus on the fixed TT-rank and precision problems of finding an approximation of the tensor train (TT) decomposition of a tensor. Note that the TT-SVD and TT-cros…
Efficient algorithms for Tucker decomposition via approximate matrix multiplication
Maolin Che, Yimin Wei, Hong Yan
This paper develops fast and efficient algorithms for computing Tucker decomposition with a given multilinear rank. By combining random projection and the power scheme, we propose…
Noda Iteration for Computing Generalized Tensor Eigenpairs
Wanli Ma, Weiyang Ding, Yimin Wei
In this paper, we propose the tensor Noda iteration (NI) and its inexact version for solving the eigenvalue problem of a particular class of tensor pairs called generalized $\mathc…
Perturbation analysis on T-eigenvalues of third-order tensors
Changxin Mo, Weiyang Ding, Yimin Wei
Perturbation analysis has emerged as a significant concern across multiple disciplines, with notable advancements being achieved, particularly in the realm of matrices. This study…
Stochastic Tensors to Stochastic Tensor Complementarity Problems
Maolin Che, Liqun Qi, Yimin Wei
The main purpose of this paper is devoted to an introduction of the stochastic tensor complementarity problem. We consider the expected residual minimization formulation of the sto…
Positive Definite Tensors to Nonlinear Complementarity Problems
Maolin Che, Liqun Qi, Yimin Wei
The main purpose of this note is to investigate some kinds of nonlinear complementarity problems (NCP). For the structured tensors, such as, symmetric positive definite tensors and…