5 papers
Deep Learning Optimization Using Self-Adaptive Weighted Auxiliary Variables
Yaru Liu, Yiqi Gu, Michael K. Ng
In this paper, we develop a new optimization framework for the least squares learning problem via fully connected neural networks or physics-informed neural networks. The gradient…
A Graph-Partitioning Based Continuous Optimization Approach to Semi-supervised Clustering Problems
Wei Liu, Xin Liu, Michael K. Ng +1
Semi-supervised clustering is a basic problem in various applications. Most existing methods require knowledge of the ideal cluster number, which is often difficult to obtain in pr…
Hyperspectral and multispectral image fusion with arbitrary resolution through self-supervised representations
Ting Wang, Zipei Yan, Jizhou Li +3
The fusion of a low-resolution hyperspectral image (LR-HSI) with a high-resolution multispectral image (HR-MSI) has emerged as an effective technique for achieving HSI super-resolu…
A -preconditioner for space fractional diffusion equation with non-separable variable coefficients
Xue-Lei Lin, Michael K. Ng
In this paper, we study a -matrix approximation based preconditioner for the linear systems arising from discretization of unsteady state Riesz space fractional diffusion equati…
A Bijective Image Retargeting Algorithm Based on Conformal Energy
Chengyang Liu, Michael K. Ng
Image retargeting, which resizes images to one with a prescribed aspect ratio by determining an optimal warping map, has gained substantial interest in imaging science. Despite sig…