17 citations · 39 across the 8 of their papers we have counts for
5 papers · 1 filter
Hybrid Kronecker Product Decomposition and Approximation
Chencheng Cai, Rong Chen, Han Xiao
Discovering the underlying low dimensional structure of high dimensional data has attracted a significant amount of researches recently and has shown to have a wide range of applic…
KoPA: Automated Kronecker Product Approximation
Chencheng Cai, Rong Chen, Han Xiao
We consider the problem of matrix approximation and denoising induced by the Kronecker product decomposition. Specifically, we propose to approximate a given matrix by the sum of a…
State Space Emulation and Annealed Sequential Monte Carlo for High Dimensional Optimization
Chencheng Cai, Rong Chen
Many high dimensional optimization problems can be reformulated into a problem of finding theoptimal state path under an equivalent state space model setting. In this article, we p…
Matrix Completion using Kronecker Product Approximation
Chencheng Cai, Rong Chen, Han Xiao
A matrix completion problem is to recover the missing entries in a partially observed matrix. Most of the existing matrix completion methods assume a low rank structure of the unde…
Individualized Group Learning
Chencheng Cai, Rong Chen, Min-ge Xie
Many massive data are assembled through collections of information of a large number of individuals in a population. The analysis of such data, especially in the aspect of individu…