5 citations · 7 across the 5 of their papers we have counts for
5 papers
Preconditioned Truncated Single-Sample Estimators for Scalable Stochastic Optimization
Tianshi Xu, Difeng Cai, Hua Huang +2
Many large-scale stochastic optimization algorithms involve repeated solutions of linear systems or evaluations of log-determinants. In these regimes, computing exact solutions is…
HiGP: A high-performance Python package for Gaussian Process
Hua Huang, Tianshi Xu, Yuanzhe Xi +1
Gaussian Processes (GPs) are flexible, nonparametric Bayesian models widely used for regression and classification because of their ability to capture complex data patterns and qua…
Data-driven Construction of Hierarchical Matrices with Nested Bases
Difeng Cai, Hua Huang, Edmond Chow +1
Hierarchical matrices provide a powerful representation for significantly reducing the computational complexity associated with dense kernel matrices. For general kernel functions,…
Efficient construction of an HSS preconditioner for symmetric positive definite matrices
Xin Xing, Hua Huang, Edmond Chow
In an iterative approach for solving linear systems with ill-conditioned, symmetric positive definite (SPD) kernel matrices, both fast matrix-vector products and fast preconditioni…
SPARC: Simulation Package for Ab-initio Real-space Calculations
Qimen Xu, Abhiraj Sharma, Benjamin Comer +5
We present SPARC: Simulation Package for Ab-initio Real-space Calculations. SPARC can perform Kohn-Sham density functional theory calculations for isolated systems such as molecule…