1 citations · 1 across the 6 of their papers we have counts for
6 papers
Sampling Complexity of TD and PPO in RKHS
Lu Zou, Wendi Ren, Weizhong Zhang +2
We revisit Proximal Policy Optimization (PPO) from a function-space perspective. Our analysis decouples policy evaluation and improvement in a reproducing kernel Hilbert space (RKH…
Kernel Multigrid: Accelerate Back-fitting via Sparse Gaussian Process Regression
Lu Zou, Liang Ding
Additive Gaussian Processes (GPs) are popular approaches for nonparametric feature selection. The common training method for these models is Bayesian Back-fitting. However, the con…
Asymptotic Theory for Linear Functionals of Kernel Ridge Regression
Rui Tuo, Lu Zou
An asymptotic theory is established for linear functionals of the predictive function given by kernel ridge regression, when the reproducing kernel Hilbert space is equivalent to a…
Improved Convergence Rate of Nested Simulation with LSE on Sieve
Ruoxue Liu, Liang Ding, Wenjia Wang +1
Nested simulation encompasses the estimation of functionals linked to conditional expectations through simulation techniques. In this paper, we treat conditional expectation as a f…
Representing Additive Gaussian Processes by Sparse Matrices
Lu Zou, Haoyuan Chen, Liang Ding
Among generalized additive models, additive Matérn Gaussian Processes (GPs) are one of the most popular for scalable high-dimensional problems. Thanks to their additive structure a…
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…