Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards accelerated rates for distributed optimization over time-varying
  networks   We study the problem of decentralized optimization over time-varying networks
with strongly convex smooth cost functions. In our approach, nodes run a
multi-step gossip procedure after making each gradient update, thus ensuring
approximate consensus at each iteration, while the outer loop is based on
accelerated Nesterov scheme. The algorithm achieves precision $\varepsilon > 0$
in $O(\sqrt{\kappa_g}\chi\log^2(1/\varepsilon))$ communication steps and
$O(\sqrt{\kappa_g}\log(1/\varepsilon))$ gradient computations at each node,
where $\kappa_g$ is the global function number and $\chi$ characterizes
connectivity of the communication network. In the case of a static network,
$\chi = 1/\gamma$ where $\gamma$ denotes the normalized spectral gap of
communication matrix $\mathbf{W}$. The complexity bound includes $\kappa_g$,
which can be significantly better than the worst-case condition number among
the nodes.

24
The categories of this paper are: dg-ga
16
The categories of this paper are: stat
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th