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Found 6 papers, 2 papers with code
Decentralized Distributed Optimization for Saddle Point Problems
We consider distributed convex-concave saddle point problems over arbitrary connected undirected networks and propose a decentralized distributed algorithm for their solution.
Distributed Optimization
Optimization and Control
Distributed, Parallel, and Cluster Computing
Improved Complexity Bounds in Wasserstein Barycenter Problem
In this paper, we focus on computational aspects of the Wasserstein barycenter problem.
Optimization and Control
Accelerated meta-algorithm for convex optimization
We propose an accelerated meta-algorithm, which allows to obtain accelerated methods for convex unconstrained minimization in different settings.
Optimization and Control
Stochastic Approximation versus Sample Average Approximation for population Wasserstein barycenters
In terms of oracle complexity (required number of stochastic gradient evaluations), both approaches are considered equivalent on average (up to a logarithmic factor).
Adaptive Gradient Descent for Convex and Non-Convex Stochastic Optimization
In this paper we propose several adaptive gradient methods for stochastic optimization.
Optimization and Control
Distributed Computation of Wasserstein Barycenters over Networks
We propose a new \cu{class-optimal} algorithm for the distributed computation of Wasserstein Barycenters over networks.
