no code implementations • 11 Feb 2022 • Muhammad I. Qureshi, Usman A. Khan
In this paper, we propose GT-GDA, a distributed optimization method to solve saddle point problems of the form: $\min_{\mathbf{x}} \max_{\mathbf{y}} \{F(\mathbf{x},\mathbf{y}) :=G(\mathbf{x}) + \langle \mathbf{y}, \overline{P} \mathbf{x} \rangle - H(\mathbf{y})\}$, where the functions $G(\cdot)$, $H(\cdot)$, and the the coupling matrix $\overline{P}$ are distributed over a strongly connected network of nodes.
no code implementations • 7 Feb 2022 • Muhammad I. Qureshi, Ran Xin, Soummya Kar, Usman A. Khan
This paper proposes AB-SAGA, a first-order distributed stochastic optimization method to minimize a finite-sum of smooth and strongly convex functions distributed over an arbitrary directed graph.
1 code implementation • 13 Aug 2020 • Muhammad I. Qureshi, Ran Xin, Soummya Kar, Usman A. Khan
In this paper, we propose Push-SAGA, a decentralized stochastic first-order method for finite-sum minimization over a directed network of nodes.
2 code implementations • 15 May 2020 • Muhammad I. Qureshi, Ran Xin, Soummya Kar, Usman A. Khan
In this report, we study decentralized stochastic optimization to minimize a sum of smooth and strongly convex cost functions when the functions are distributed over a directed network of nodes.