Liang Ding

12 papers A* 1Misc 1Journal 10
YearRankTypeTitle / Venue / Authors
2024 J jnl
A General Theory for Kernel Packets: from state space model to compactly supported basis.
CoRR
Liang Ding, Rui Tuo
2024 J jnl
Kernel Multigrid: Accelerate Back-fitting via Sparse Gaussian Process Regression.
CoRR
Lu Zou, Liang Ding
2024 J jnl
Sample and Computationally Efficient Stochastic Kriging in High Dimensions.
Oper. Res.
Liang Ding, Xiaowei Zhang
2023 J jnl
Representing Additive Gaussian Processes by Sparse Matrices.
CoRR
Lu Zou, Haoyuan Chen, Liang Ding
2022 J jnl
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations.
CoRR
Haoyuan Chen, Liang Ding, Rui Tuo
2022 J jnl
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations.
J. Mach. Learn. Res.
Haoyuan Chen, Liang Ding, Rui Tuo
2021 J jnl
A Sparse Expansion For Deep Gaussian Processes.
CoRR
Liang Ding, Rui Tuo, Shahin Shahrampour
2021 J jnl
High-Dimensional Simulation Optimization via Brownian Fields and Sparse Grids.
CoRR
Liang Ding, Rui Tuo, Xiaowei Zhang
2020 A* conf
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features.
ICML
Liang Ding, Rui Tuo, Shahin Shahrampour
2020 J jnl
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features.
CoRR
Liang Ding, Rui Tuo, Shahin Shahrampour
2020 J jnl
Overcoming the Curse of Dimensionality in Density Estimation with Mixed Sobolev GANs.
CoRR
Liang Ding, Rui Tuo, Shahin Shahrampour
2016 Misc conf
Sequential sampling for Bayesian robust ranking and selection.
WSC
Xiaowei Zhang, Liang Ding