Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Distributed Principal Component Analysis with Limited Communication   We study efficient distributed algorithms for the fundamental problem of
principal component analysis and leading eigenvector computation on the sphere,
when the data are randomly distributed among a set of computational nodes. We
propose a new quantized variant of Riemannian gradient descent to solve this
problem, and prove that the algorithm converges with high probability under a
set of necessary spherical-convexity properties. We give bounds on the number
of bits transmitted by the algorithm under common initialization schemes, and
investigate the dependency on the problem dimension in each case.

20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
16
The categories of this paper are: stat
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin