3 citations · 3 across the 4 of their papers we have counts for
5 papers
Optimal detection of general moment changes: Simultaneous mean and covariance change detection and beyond
Xiaokai Luo, Chenghao Xu, Haotian Xu +2
We study multiple change-point detection in multivariate time series whose distributions change in a piecewise constant manner. Distributional changes can manifest across different…
Online Change Point Detection for Multivariate Inhomogeneous Poisson Processes Time Series
Xiaokai Luo, Haotian Xu, Carlos Misael Madrid Padilla +1
We study online change point detection for multivariate inhomogeneous Poisson point process time series. This setting arises commonly in applications such as earthquake seismology,…
Optimal Bias-variance Tradeoff in Matrix and Tensor Estimation
Shivam Kumar, Xiaokai Luo, Haotian Xu +3
We study matrix and tensor denoising when the underlying signal is \textbf{not} necessarily low-rank. In the tensor setting, we observe \[ Y = X^\ast + Z \in \mathbb{R}^{p_1 \times…
Dense ReLU Neural Networks for Temporal-spatial Model
Carlos Misael Madrid Padilla, Zhi Zhang, Xiaokai Luo +2
In this paper, we focus on fully connected deep neural networks utilizing the Rectified Linear Unit (ReLU) activation function for nonparametric estimation. We derive non-asymptoti…
Optimal Change-point Testing for High-dimensional Linear Models with Temporal Dependence
Zifeng Zhao, Xiaokai Luo, Zongge Liu +1
In this paper, we study change-point testing for high-dimensional linear models, an important problem that has not been well explored in the literature. Specifically, we propose a…