Decentralized optimization with affine constraints over time-varying networks

Demyan Yarmoshik (), Alexander Rogozin () and Alexander Gasnikov ()
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Demyan Yarmoshik: Moscow Institute of Physics and Technology
Alexander Rogozin: Moscow Institute of Physics and Technology
Alexander Gasnikov: Moscow Institute of Physics and Technology

Computational Management Science, 2024, vol. 21, issue 1, No 10, 23 pages

Abstract: Abstract The decentralized optimization paradigm assumes that each term of a finite-sum objective is privately stored by the corresponding agent. Agents are only allowed to communicate with their neighbors in the communication graph. We consider the case when the agents additionally have local affine constraints and the communication graph can change over time. We provide the first linearly convergent decentralized algorithm for time-varying networks by generalizing the optimal decentralized algorithm ADOM to the case of affine constraints. We show that its rate of convergence is optimal for first-order methods by providing the lower bounds for the number of communications and oracle calls.

Keywords: Convex optimization; Decentralized optimization; Affine constraints; Time-varying networks (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10287-023-00492-w

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