9 citations · 12 across the 8 of their papers we have counts for
9 papers
Fully-Connected Tensor Network Decomposition for Robust Tensor Completion Problem
Yun-Yang Liu, Xi-Le Zhao, Guang-Jing Song +2
The robust tensor completion (RTC) problem, which aims to reconstruct a low-rank tensor from partially observed tensor contaminated by a sparse tensor, has received increasing atte…
Low Rank Pure Quaternion Approximation for Pure Quaternion Matrices
Guangjing Song, Weiyang Ding, Michael K. Ng
Quaternion matrices are employed successfully in many color image processing applications. In particular, a pure quaternion matrix can be used to represent red, green and blue chan…
Tensor Completion by Multi-Rank via Unitary Transformation
Guang-Jing Song, Michael K. Ng, Xiongjun Zhang
One of the key problems in tensor completion is the number of uniformly random sample entries required for recovery guarantee. The main aim of this paper is to study $n_1 \times n_…
Riemannian Conjugate Gradient Descent Method for Third-Order Tensor Completion
Guang-Jing Song, Xue-Zhong Wang, Michael K. Ng
The goal of tensor completion is to fill in missing entries of a partially known tensor under a low-rank constraint. In this paper, we mainly study low rank third-order tensor comp…
Tangent Space Based Alternating Projections for Nonnegative Low Rank Matrix Approximation
Guangjing Song, Michael K. Ng, Tai-Xiang Jiang
In this paper, we develop a new alternating projection method to compute nonnegative low rank matrix approximation for nonnegative matrices. In the nonnegative low rank matrix appr…
Nonnegative Low Rank Tensor Approximation and its Application to Multi-dimensional Images
Tai-Xiang Jiang, Michael K. Ng, Junjun Pan +1
The main aim of this paper is to develop a new algorithm for computing nonnegative low rank tensor approximation for nonnegative tensors that arise in many multi-dimensional imagin…
Fast Alternating Projections on Manifolds Based on Tangent Spaces
Guangjing Song, Michael K. Ng
In this paper, we study alternating projections on nontangential manifolds based on the tangent spaces. The main motivation is that the projection of a point onto a manifold can be…
Nonnegative Low Rank Matrix Approximation for Nonnegative Matrices
Guang-Jing Song, Michael Kwok-Po Ng
This paper describes a new algorithm for computing Nonnegative Low Rank Matrix (NLRM) approximation for nonnegative matrices. Our approach is completely different from classical no…
Robust Tensor Completion Using Transformed Tensor SVD
Guangjing Song, Michael K. Ng, Xiongjun Zhang
In this paper, we study robust tensor completion by using transformed tensor singular value decomposition (SVD), which employs unitary transform matrices instead of discrete Fourie…