3 papers
stat.ME2025
Functional Change Point Detection via Adjacent Deviation Subspace
Luoyao Yu, Long Feng, Xuehu Zhu
This paper develops the concept of the Adjacent Deviation Subspace (ADS), a novel framework for reducing infinite-dimensional functional data into finite-dimensional vector or scal…
stat.ME2025
A Spatial-Sign based Direct Approach for High Dimensional Sparse Quadratic Discriminant Analysis
Anqing Shen, Long Feng
In this paper, we study the problem of high-dimensional sparse quadratic discriminant analysis (QDA). We propose a novel classification method, termed SSQDA, which is constructed v…
stat.ME2025
Spatial Sign based Direct Sparse Linear Discriminant Analysis for High Dimensional Data
Dan Zhuang, Long Feng
This paper investigates the robust linear discriminant analysis (LDA) problem with elliptical distributions in high-dimensional data. We propose a robust classification method, nam…