8 citations · 26 across the 13 of their papers we have counts for
5 papers · 1 filter
Sample and Computationally Efficient Stochastic Kriging in High Dimensions
Liang Ding, Xiaowei Zhang
Stochastic kriging has been widely employed for simulation metamodeling to predict the response surface of complex simulation models. However, its use is limited to cases where the…
A projected gradient method for sparsity regularization
Liang Ding, Weimin Han
The non-convex regularization has attracted attention in the field of sparse recovery. One way to obtain a minimizer of th…
sparsity regularization for nonlinear ill-posed problems
Liang Ding, Weimin Han
In this paper, we consider the sparsity regularization with parameter for nonlinear ill-posed inverse problems. We investi…
High-Dimensional Non-Parametric Density Estimation in Mixed Smooth Sobolev Spaces
Liang Ding, Lu Zou, Wenjia Wang +2
Density estimation plays a key role in many tasks in machine learning, statistical inference, and visualization. The main bottleneck in high-dimensional density estimation is the p…
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features
Liang Ding, Rui Tuo, Shahin Shahrampour
Despite their success, kernel methods suffer from a massive computational cost in practice. In this paper, in lieu of commonly used kernel expansion with respect to inputs, we…