Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Decentralized Approximate Newton Methods for Convex Optimization on
  Networked Systems   In this paper, a class of Decentralized Approximate Newton (DEAN) methods for
addressing convex optimization on a networked system are developed, where nodes
in the networked system seek for a consensus that minimizes the sum of their
individual objective functions through local interactions only. The proposed
DEAN algorithms allow each node to repeatedly perform a local approximate
Newton update, which leverages tracking the global Newton direction and
dissipating the discrepancies among the nodes. Under less restrictive problem
assumptions in comparison with most existing second-order methods, the DEAN
algorithms enable the nodes to reach a consensus that can be arbitrarily close
to the optimum. Moreover, for a particular DEAN algorithm, the nodes linearly
converge to a common suboptimal solution with an explicit error bound. Finally,
simulations demonstrate the competitive performance of DEAN in convergence
speed, accuracy, and efficiency.

18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con