5 citations · 7 across the 4 of their papers we have counts for
7 papers
Residual Enhanced Multi-Hypergraph Neural Network
Jing Huang, Xiaolin Huang, Jie Yang
Hypergraphs are a generalized data structure of graphs to model higher-order correlations among entities, which have been successfully adopted into various research domains. Meanwh…
Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels
Qin Luo, Kun Fang, Jie Yang +1
Random Fourier Features (RFF) demonstrate wellappreciated performance in kernel approximation for largescale situations but restrict kernels to be stationary and positive definite.…
Multi-Level Graph Convolutional Network with Automatic Graph Learning for Hyperspectral Image Classification
Sheng Wan, Chen Gong, Shirui Pan +2
Nowadays, deep learning methods, especially the Graph Convolutional Network (GCN), have shown impressive performance in hyperspectral image (HSI) classification. However, the curre…
Analysis of Regularized Least Squares in Reproducing Kernel Krein Spaces
Fanghui Liu, Lei Shi, Xiaolin Huang +2
In this paper, we study the asymptotic properties of regularized least squares with indefinite kernels in reproducing kernel Krein spaces (RKKS). By introducing a bounded hyper-sph…
Sparse Generalized Canonical Correlation Analysis: Distributed Alternating Iteration based Approach
Jia Cai, Kexin Lv, Junyi Huo +2
Sparse canonical correlation analysis (CCA) is a useful statistical tool to detect latent information with sparse structures. However, sparse CCA works only for two datasets, i.e.,…
Real-time Image Smoothing via Iterative Least Squares
Wei Liu, Pingping Zhang, Xiaolin Huang +3
Edge-preserving image smoothing is a fundamental procedure for many computer vision and graphic applications. There is a tradeoff between the smoothing quality and the processing s…