Aug 25, 2022 · In this paper, we study the distributed optimization problem using approximate first-order information. We suppose the agent can repeatedly call an inexact ...
In this paper, we study the distributed optimization problem using approximate first-order information. We suppose the agent can repeatedly call an inexact ...
In this paper, we study the distributed optimization problem using approximate first-order information. We suppose the agent can repeatedly call an inexact ...
Aug 25, 2022 · Abstract: In this paper, we study the distributed optimization problem using approximate first-order information.
Summary: In this paper, we study the distributed optimization problem using approximate first-order information. We suppose the agent can repeatedly call an ...
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This paper presents several conditions on the inexactness of the local oracles to ensure an exact convergence of the iterative sequences towards the global ...
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In this paper, we study the distributed optimization problem using approximate first-order information. We suppose the agent can repeatedly call an inexact ...
Oct 22, 2024 · A dynamical quantum model assigns n eigenstate to a specified observable even when no mea- surement is made, and gives a stochastic evolution ...
Thus, it is natural for us to investigate the behavior of distributed first-order optimization methods working with an inexact oracle. For this purpose, we ...
In this paper, we propose a new method based on the Sliding Algorithm from Lan (2016, 2019) for the convex composite optimization problem that includes two ...