Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Distributed Stochastic Subgradient Optimization Algorithms Over Random
  and Noisy Networks   We study distributed stochastic optimization by networked nodes to
cooperatively minimize a sum of convex cost functions. The network is modeled
by a sequence of time-varying random digraphs with each node representing a
local optimizer and each edge representing a communication link. We consider
the distributed subgradient optimization algorithm with noisy measurements of
local cost functions' subgradients, additive and multiplicative noises among
information exchanging between each pair of nodes. By stochastic Lyapunov
method, convex analysis, algebraic graph theory and martingale convergence
theory, it is proved that if the local subgradient functions grow linearly and
the sequence of digraphs is conditionally balanced and uniformly conditionally
jointly connected, then proper algorithm step sizes can be designed so that all
nodes' states converge to the global optimal solution almost surely.

7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
30
The categories of this paper are: q-alg
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
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The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int