44 citations · 76 across the 7 of their papers we have counts for
7 papers
Efficient algorithms for collecting the statistics of large-scale IP address data
Hui Liu, Yi Cao, Zehan Cai +2
Compiling the statistics of large-scale IP address data is an essential task in network traffic measurement. The statistical results are used to evaluate the potential impact of us…
Efficient proximal gradient algorithms for joint graphical lasso
Jie Chen, Ryosuke Shimmura, Joe Suzuki
We consider learning an undirected graphical model from sparse data. While several efficient algorithms have been proposed for graphical lasso (GL), the alternating direction metho…
Graph coarsening: From scientific computing to machine learning
Jie Chen, Yousef Saad, Zechen Zhang
The general method of graph coarsening or graph reduction has been a remarkably useful and ubiquitous tool in scientific computing and it is now just starting to have a similar imp…
A Posteriori Error Estimate for Computing by Using the Lanczos Method
Jie Chen, Yousef Saad
An outstanding problem when computing a function of a matrix, , by using a Krylov method is to accurately estimate errors when convergence is slow. Apart from the case of the…
Linear-Cost Covariance Functions for Gaussian Random Fields
Jie Chen, Michael L. Stein
Gaussian random fields (GRF) are a fundamental stochastic model for spatiotemporal data analysis. An essential ingredient of GRF is the covariance function that characterizes the j…
Symmetric low-rank representation for subspace clustering
Jie Chen, Haixian Zhang, Hua Mao +2
We propose a symmetric low-rank representation (SLRR) method for subspace clustering, which assumes that a data set is approximately drawn from the union of multiple subspaces. The…
Stochastic approximation of score functions for Gaussian processes
Michael L. Stein, Jie Chen, Mihai Anitescu
We discuss the statistical properties of a recently introduced unbiased stochastic approximation to the score equations for maximum likelihood calculation for Gaussian processes. U…