2 citations · 2 across the 5 of their papers we have counts for
5 papers
Coupling Matrix Manifolds and Their Applications in Optimal Transport
Dai Shi, Junbin Gao, Xia Hong +2
Optimal transport (OT) is a powerful tool for measuring the distance between two defined probability distributions. In this paper, we develop a new manifold named the coupling matr…
Sparse Least Squares Low Rank Kernel Machines
Di Xu, Manjing Fang, Xia Hong +1
A general framework of least squares support vector machine with low rank kernels, referred to as LR-LSSVM, is introduced in this paper. The special structure of low rank kernels w…
l1-norm Penalized Orthogonal Forward Regression
Xia Hong, Sheng Chen, Yi Guo +1
A l1-norm penalized orthogonal forward regression (l1-POFR) algorithm is proposed based on the concept of leaveone- out mean square error (LOOMSE). Firstly, a new l1-norm penalized…
Low Rank Representation on Riemannian Manifold of Square Root Densities
Yifan Fu, Junbin Gao, Xia Hong +1
In this paper, we present a novel low rank representation (LRR) algorithm for data lying on the manifold of square root densities. Unlike traditional LRR methods which rely on the…
Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization
Yanfeng Sun, Junbin Gao, Xia Hong +2
Tensors or multiarray data are generalizations of matrices. Tensor clustering has become a very important research topic due to the intrinsically rich structures in real-world mult…