Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Optimal Subsampling for High-dimensional Ridge Regression   We investigate the feature compression of high-dimensional ridge regression
using the optimal subsampling technique. Specifically, based on the basic
framework of random sampling algorithm on feature for ridge regression and the
A-optimal design criterion, we first obtain a set of optimal subsampling
probabilities. Considering that the obtained probabilities are uneconomical, we
then propose the nearly optimal ones. With these probabilities, a two step
iterative algorithm is established which has lower computational cost and
higher accuracy. We provide theoretical analysis and numerical experiments to
support the proposed methods. Numerical results demonstrate the decent
performance of our methods.

10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol