1 citations · 3 across the 10 of their papers we have counts for
10 papers
High dimensional matrix estimation through elliptical factor models
Xinyue Xu, Huifang Ma, Hongfei Wang +1
Elliptical factor models play a central role in modern high-dimensional data analysis, particularly due to their ability to capture heavy-tailed and heterogeneous dependence struct…
A Nonparametric Statistics Approach to Feature Selection in Deep Neural Networks with Theoretical Guarantees
Junye Du, Zhenghao Li, Zhutong Gu +1
This paper tackles the problem of feature selection in a highly challenging setting: , where is…
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…
High Dimensional Sparse Canonical Correlation Analysis for Elliptical Symmetric Distributions
Chengde Qian, Yanhong Liu, Long Feng
This paper proposes a robust high-dimensional sparse canonical correlation analysis (CCA) method for investigating linear relationships between two high-dimensional random vectors,…
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…
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…
Adaptive Rank-based Tests for High Dimensional Mean Problems
Yu Zhang, Long Feng
The Wilcoxon signed-rank test and the Wilcoxon-Mann-Whitney test are commonly employed in one sample and two sample mean tests for one-dimensional hypothesis problems. For high-dim…
Projected Robust PCA with Application to Smooth Image Recovery
Long Feng, Junhui Wang
Most high-dimensional matrix recovery problems are studied under the assumption that the target matrix has certain intrinsic structures. For image data related matrix recovery prob…
Power Comparison between High Dimensional t-Test, Sign, and Signed Rank Tests
Long Feng
In this paper, we propose a power comparison between high dimensional t-test, sign and signed rank test for the one sample mean test. We show that the high dimensional signed rank…
Sorted Concave Penalized Regression
Long Feng, Cun-Hui Zhang
The Lasso is biased. Concave penalized least squares estimation (PLSE) takes advantage of signal strength to reduce this bias, leading to sharper error bounds in prediction, coeffi…