4 citations · 11 across the 8 of their papers we have counts for
5 papers · 1 filter
Randomized Feasibility-Update Algorithms for Stochastic Variational Inequality Problems
Abhishek Chakraborty, Angelia Nedić
This paper considers stochastic monotone variational inequalities whose feasible region is the intersection of a (possibly infinite) number of convex functional level sets. A proje…
Popov Mirror-Prox for solving Variational Inequalities
Abhishek Chakraborty, Angelia Nedić
We consider the mirror-prox algorithm for solving monotone Variational Inequality (VI) problems. As the mirror-prox algorithm is not practically implementable, except in special in…
An Accelerated Distributed Stochastic Gradient Method with Momentum
Kun Huang, Shi Pu, Angelia Nedić
In this paper, we introduce an accelerated distributed stochastic gradient method with momentum for solving the distributed optimization problem, where a group of agents collab…
Randomized Feasibility-Update Algorithms for Variational Inequality Problems
Abhishek Chakraborty, Angelia Nedić
This paper considers a variational inequality (VI) problem arising from a game among multiple agents, where each agent aims to minimize its own cost function subject to its constra…
Projected Push-Pull For Distributed Constrained Optimization Over Time-Varying Directed Graphs (extended version)
Orhan Eren Akgün, Arif Kerem Dayı, Stephanie Gil +1
We introduce the Projected Push-Pull algorithm that enables multiple agents to solve a distributed constrained optimization problem with private cost functions and global constrain…