2 citations · 5 across the 10 of their papers we have counts for
8 papers · 1 filter
Statistical Theory of Multi-stage Newton Iteration Algorithm for Online Continual Learning
Xinjia Lu, Chuhan Wang, Qian Zhao +2
We focus on the critical challenge of handling non-stationary data streams in online continual learning environments, where constrained storage capacity prevents complete retention…
Corrected kernel principal component analysis for model structural change detection
Luoyao Yu, Lixing Zhu, Ruoqing Zhu +1
This paper develops a method to detect model structural changes by applying a Corrected Kernel Principal Component Analysis (CKPCA) to construct the so-called central distribution…
Multiple change point detection in tensors
Jiaqi Huang, Junhui Wang, Xuehu Zhu +1
This paper proposes a criterion for detecting change structures in tensor data. To accommodate tensor structure with structural mode that is not suitable to be equally treated and…
Detecting multiple change points: a PULSE criterion
Wenbiao Zhao, Xuehu Zhu, Lixing Zhu
The research described herewith investigates detecting change points of means and of variances in a sequence of observations. The number of change points can be divergent at certai…
Adaptive-to-model hybrid of tests for regressions
Lingzhu Li, Xuehu Zhu, Lixing Zhu
In model checking for regressions, nonparametric estimation-based tests usually have tractable limiting null distributions and are sensitive to oscillating alternative models, but…
A projection-based adaptive-to-model test for regressions
Falong Tan, Xuehu Zhu, Lixing Zhu
A longstanding problem of existing empirical process-based tests for regressions is that when the number of covariates is greater than one, they either have no tractable limiting n…
An adaptive-to-model test for partially parametric single-index models
Xuehu Zhu, Xu Guo, Lixing Zhu
Residual marked empirical process-based tests are commonly used in regression models. However, they suffer from data sparseness in high-dimensional space when there are many covari…
Dimension reduction-based significance testing in nonparametric regression
Xuehu Zhu, Lixing Zhu
A dimension reduction-based adaptive-to-model test is proposed for significance of a subset of covariates in the context of a nonparametric regression model. Unlike existing local…