20 citations · 54 across the 15 of their papers we have counts for
9 papers · 1 filter
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…
Orthogonal Nonnegative Tucker Decomposition
Junjun Pan, Michael K. Ng, Ye Liu +2
In this paper, we study the nonnegative tensor data and propose an orthogonal nonnegative Tucker decomposition (ONTD). We discuss some properties of ONTD and develop a convex relax…
Bilinear Constraint based ADMM for Mixed Poisson-Gaussian Noise Removal
Jie Zhang, Yuping Duan, Yue Lu +2
In this paper, we propose new operator-splitting algorithms for the total variation regularized infimal convolution (TV-IC) model [4] in order to remove mixed Poisson-Gaussian(MPG)…
Framelet Representation of Tensor Nuclear Norm for Third-Order Tensor Completion
Tai-Xiang Jiang, Michael K. Ng, Xi-Le Zhao +1
The main aim of this paper is to develop a framelet representation of the tensor nuclear norm for third-order tensor completion. In the literature, the tensor nuclear norm can be c…
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…
Tucker Decomposition Network: Expressive Power and Comparison
Ye Liu, Junjun Pan, Michael Ng
Deep neural networks have achieved a great success in solving many machine learning and computer vision problems. The main contribution of this paper is to develop a deep network b…