Feature Screening with Conditional Rank Utility for Big-Data Classification-Reference-Cited by-同舟云学术

Feature Screening with Conditional Rank Utility for Big-Data Classification

Published:2023-04-18 Issue: Volume: Page:1-11
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Li Xingxiang¹,Xu Chen²³^ORCID

Affiliation:

1. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China

2. Department of Mathematics and Statistics, University of Ottawa, Ottawa, Canada

3. Department of Mathematics and Fundamental Research, Peng Cheng Laboratory, Shenzhen, China

Funder

National Key Research and Development Program of China

Major Key Project of Peng Cheng Laboratory

Natural Science Engineering Research Council of Canada

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2023.2195976

Reference28 articles.

1. Distributed testing and estimation under sparse high dimensional models

2. Robust rank screening for ultrahigh dimensional discriminant analysis

3. Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis

4. Dua D. and Graff C. (2019) “UCI Machine Learning Repository ” University of California Irvine School of Information and Computer Sciences. Available at http://archive.ics.uci.edu/ml.

5. High-dimensional classification using features annealed independence rules

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Network alternating direction method of multipliers for ultrahigh‐dimensional decentralised federated learning;Stat;2024-04-04

2. Distributed Sparse Precision Matrix Estimation via Alternating Block-Based Gradient Descent;Mathematics;2024-02-22

3. Structure learning via unstructured kernel-based M-estimation;Electronic Journal of Statistics;2023-01-01