8 citations · 17 across the 14 of their papers we have counts for
14 papers
Generalized Deep Regression for Repeated Measurements
Kexuan Li
In this paper, we study the estimation of a marginal regression function from independent units with repeated binary, count, or continuous responses using ReLU deep neural networks…
A Deep Learning Model for Spatially Clustered Data via Differentiable Cluster Assignment
Kexuan Li, Weidong Ma
We consider nonparametric regression when the association between a response and its covariates changes across an unknown partition of a spatial domain. The proposed estimator lear…
A Continuous-Weighted Win Ratio for Hierarchical Composite Endpoints
Kexuan Li
Hierarchical composite endpoints are commonly used in clinical trials when component out- comes differ in clinical importance. The win ratio compares patients across treatment grou…
Estimation and Hypothesis Testing of Derivatives in Smoothing Spline ANOVA Models
Ruiqi Liu, Kexuan Li, Meng Li
Within the framework of smoothing spline ANOVA, we propose a plug-in kernel ridge regression estimator to estimate the derivatives of the underlying multivariate regression functio…
Multivariate Rank-Based Analysis of Multiple Endpoints in Clinical Trials: A Global Test Approach
Kexuan Li, Lingli Yang, Shaofei Zhao +3
Clinical trials often involve the assessment of multiple endpoints to comprehensively evaluate the efficacy and safety of interventions. In the work, we consider a global nonparame…
On the Confidence Intervals in Bioequivalence Studies
Kexuan Li, Susie Sinks, Peng Sun +1
A bioequivalence study is a type of clinical trial designed to compare the biological equivalence of two different formulations of a drug. Such studies are typically conducted in c…
Semiparametric Regression for Spatial Data via Deep Learning
Kexuan Li, Jun Zhu, Anthony R. Ives +2
In this work, we propose a deep learning-based method to perform semiparametric regression analysis for spatially dependent data. To be specific, we use a sparsely connected deep n…
Variable selection for nonlinear Cox regression model via deep learning
Kexuan Li
Variable selection problem for the nonlinear Cox regression model is considered. In survival analysis, one main objective is to identify the covariates that are associated with the…
Deep Feature Screening: Feature Selection for Ultra High-Dimensional Data via Deep Neural Networks
Kexuan Li, Fangfang Wang, Lingli Yang +1
The applications of traditional statistical feature selection methods to high-dimension, low sample-size data often struggle and encounter challenging problems, such as overfitting…
Calibrating multi-dimensional complex ODE from noisy data via deep neural networks
Kexuan Li, Fangfang Wang, Ruiqi Liu +2
Ordinary differential equations (ODEs) are widely used to model complex dynamics that arises in biology, chemistry, engineering, finance, physics, etc. Calibration of a complicated…
A Computationally Efficient Classification Algorithm in Posterior Drift Model: Phase Transition and Minimax Adaptivity
Ruiqi Liu, Kexuan Li, Zuofeng Shang
In massive data analysis, training and testing data often come from very different sources, and their probability distributions are not necessarily identical. A feature example is…
On the Convergence Rate of the Quasi- to Stationary Distribution for the Shiryaev-Roberts Diffusion
Kexuan Li, Aleksey S. Polunchenko
For the classical Shiryaev--Roberts martingale diffusion considered on the interval , where is a given absorbing boundary, it is shown that the rate of convergence of…
Analytic Evaluation of the Fractional Moments for the Quasi-Stationary Distribution of the Shiryaev Martingale on an Interval
Kexuan Li, Aleksey S. Polunchenko, Andrey Pepelyshev
We consider the quasi-stationary distribution of the classical Shiryaev diffusion restricted to the interval with absorption at a fixed . We derive analytically a clos…
Nonparametric Inference under B-bits Quantization
Kexuan Li, Ruiqi Liu, Ganggang Xu +1
Statistical inference based on lossy or incomplete samples is often needed in research areas such as signal/image processing, medical image storage, remote sensing, signal transmis…