4 citations · 9 across the 10 of their papers we have counts for
12 papers
Renewing Iterative Self-labeling Domain Adaptation with Application to the Spine Motion Prediction
Gecheng Chen, Yu Zhou, Xudong Zhang +1
The area of transfer learning comprises supervised machine learning methods that cope with the issue when the training and testing data have different input feature spaces or distr…
Hypothesis Tests with Functional Data for Surface Quality Change Detection in Surface Finishing Processes
Shilan Jin, Rui Tuo, Akash Tiwari +5
This work is concerned with providing a principled decision process for stopping or tool-changing in a surface finishing process. The decision process is supposed to work for produ…
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations
Haoyuan Chen, Liang Ding, Rui Tuo
We develop an exact and scalable algorithm for one-dimensional Gaussian process regression with Matérn correlations whose smoothness parameter is a half-integer. The proposed a…
High-Dimensional Simulation Optimization via Brownian Fields and Sparse Grids
Liang Ding, Rui Tuo, Xiaowei Zhang
High-dimensional simulation optimization is notoriously challenging. We propose a new sampling algorithm that converges to a global optimal solution and suffers minimally from the…
A Reproducing Kernel Hilbert Space Approach to Functional Calibration of Computer Models
Rui Tuo, Shiyuan He, Arash Pourhabib +2
This paper develops a frequentist solution to the functional calibration problem, where the value of a calibration parameter in a computer model is allowed to vary with the value o…
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…