Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Eigenvector-based sparse canonical correlation analysis: Fast
  computation for estimation of multiple canonical vectors   Classical canonical correlation analysis (CCA) requires matrices to be low
dimensional, i.e. the number of features cannot exceed the sample size. Recent
developments in CCA have mainly focused on the high-dimensional setting, where
the number of features in both matrices under analysis greatly exceeds the
sample size. These approaches impose penalties in the optimization problems
that are needed to be solve iteratively, and estimate multiple canonical
vectors sequentially. In this work, we provide an explicit link between sparse
multiple regression with sparse canonical correlation analysis, and an
efficient algorithm that can estimate multiple canonical pairs simultaneously
rather than sequentially. Furthermore, the algorithm naturally allows parallel
computing. These properties make the algorithm much efficient. We provide
theoretical results on the consistency of canonical pairs. The algorithm and
theoretical development are based on solving an eigenvectors problem, which
significantly differentiate our method with existing methods. Simulation
results support the improved performance of the proposed approach. We apply
eigenvector-based CCA to analysis of the GTEx thyroid histology images,
analysis of SNPs and RNA-seq gene expression data, and a microbiome study. The
real data analysis also shows improved performance compared to traditional
sparse CCA.

18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
1
The categories of this paper are: cs
36
The categories of this paper are: cmp-lg
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat