Matches in SemOpenAlex for { <https://semopenalex.org/work/W2896735367> ?p ?o ?g. }
- W2896735367 abstract "In this paper, we provide a distributed optimization algorithm, termed as TV-$mathcal{AB}$, that minimizes a sum of convex functions over time-varying, random directed graphs. Contrary to the existing work, the algorithm we propose does not require eigenvector estimation to estimate the (non-$mathbf{1}$) Perron eigenvector of a stochastic matrix. Instead, the proposed approach relies on a novel information mixing approach that exploits both row- and column-stochastic weights to achieve agreement towards the optimal solution when the underlying graph is directed. We show that TV-$mathcal{AB}$ converges linearly to the optimal solution when the global objective is smooth and strongly-convex, and the underlying time-varying graphs exhibit bounded connectivity, i.e., a union of every $C$ consecutive graphs is strongly-connected. We derive the convergence results based on the stability analysis of a linear system of inequalities along with a matrix perturbation argument. Simulations confirm the findings in this paper." @default.
- W2896735367 created "2018-10-26" @default.
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- W2896735367 creator A5033024261 @default.
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- W2896735367 date "2018-10-17" @default.
- W2896735367 modified "2023-10-18" @default.
- W2896735367 title "Optimization over time-varying directed graphs with row and column-stochastic matrices" @default.
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