Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Asynchronous Decentralized Successive Convex Approximation   We study decentralized asynchronous multiagent optimization over networks,
modeled as static (possibly directed) graphs. The optimization problem consists
of minimizing a (possibly nonconvex) smooth function--the sum of the agents'
local costs--plus a convex (possibly nonsmooth) regularizer, subject to convex
constraints. Agents can perform their local computations as well as communicate
with their immediate neighbors at any time, without any form of coordination or
centralized scheduling; furthermore, when solving their local subproblems, they
can use outdated information from their neighbors. We propose the first
distributed asynchronous algorithm, termed ASY-DSCA, that converges at an
R-linear rate to the optimal solution of convex problems whose objective
function satisfies a general error bound condition; this condition is weaker
than the more frequently used strong convexity, and it is satisfied by several
empirical risk functions that are not strongly convex; examples include LASSO
and logistic regression problems. When the objective function is nonconvex,
ASY-DSCA converges to a stationary solution of the problem at a sublinear rate.

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The categories of this paper are: adap-org
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The categories of this paper are: cs
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The categories of this paper are: q-fin
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The categories of this paper are: supr-con
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The categories of this paper are: plasm-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: stat
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The categories of this paper are: dg-ga
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The categories of this paper are: ao-sci
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The categories of this paper are: chem-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: alg-geom
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The categories of this paper are: econ
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The categories of this paper are: math-ph
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The categories of this paper are: q-alg
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The categories of this paper are: comp-gas