High-dimensional Statistics
High-Dimensional Statistics is a branch of statistical science that focuses on the development and analysis of methods for inference and prediction when the number of variables or parameters approaches or exceeds the number of observations, thereby distinguishing it from classical statistics by addressing the challenges posed by large-dimensional data spaces.
1.6K
Publications
129.7K
Citations
3.1K
Authors
1.1K
Institutions
Publications per year
2017–2026
602
Parents
1.6K
Regularized Discriminant Analysis
Jerome H. Friedman · Journal of the American Statistical Association · 1989 · 2.3K citations · Full text
Integrating structured biological data by Kernel Maximum Mean Discrepancy
Karsten Borgwardt, Arthur Gretton, Malte J. Rasch et al. · Bioinformatics · 2006 · 1.7K citations · Full text
1–5 of 1.6K
3.1K
19
h-index
18
h-index
Massachusetts Institute of Technology, United States
17 publications · 1.8K citations
15
h-index
13
h-index
12
h-index
1–5 of 3.1K
1.1K
Stanford University
Stanford, United States
33 h-index
104 publications
14.5K citations
Princeton University
Princeton, United States
31 h-index
95 publications
15.7K citations
University of Pennsylvania
Philadelphia, United States
28 h-index
61 publications
6K citations
University of California, Berkeley
Berkeley, United States
27 h-index
63 publications
5.6K citations
Carnegie Mellon University
Pittsburgh, United States
26 h-index
81 publications
12.2K citations

University of Minnesota
Minneapolis, United States
25 h-index
56 publications
5.4K citations

Pennsylvania State University
State College, United States
24 h-index
41 publications
4.2K citations
Massachusetts Institute of Technology
Cambridge, United States
23 h-index
67 publications
4.2K citations
1–8 of 1.1K
110 publications · 13.2K citations
53
h-index
80 publications · 10.1K citations
41
h-index
Repository · 165 publications · 7.3K citations
36
h-index
41 publications · 2.8K citations
26
h-index
46 publications · 2.2K citations
25
h-index
1–5