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20202023
most citedAsymptotic properties of dual averaging algorithm for constrained distributed stochastic optimization

3 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

math.OC2023

A Variance-Reduced Aggregation Based Gradient Tracking method for Distributed Optimization over Directed Networks

Shengchao Zhao, Siyuan Song, Yongchao Liu

This paper studies the distributed optimization problem over directed networks with noisy information-sharing. To resolve the imperfect communication issue over directed networks,…

math.OC2022

Numerical Methods for Distributed Stochastic Compositional Optimization Problems with Aggregative Structure

Shengchao Zhao, Yongchao Liu

The paper studies the distributed stochastic compositional optimization problems over networks, where all the agents' inner-level function is the sum of each agent's private expect…

math.OC2022

Distributed Stochastic Compositional Optimization Problems over Directed Networks

Shengchao Zhao, Yongchao Liu

We study the distributed stochastic compositional optimization problems over directed communication networks in which agents privately own a stochastic compositional objective func…

math.OC2022

Stochastic Approximation Based Confidence Regions for Stochastic Variational Inequalities

Wuwenqing Yan, Yongchao Liu

The sample average approximation (SAA) and the stochastic approximation (SA) are two popular schemes for solving the stochastic variational inequalities problem (SVIP). In the past…

math.OC2021

Asymptotic Properties of - Method with Diminishing Stepsize

Shengchao Zhao, Yongchao Liu

The popular /push-pull method for distributed optimization problem may unify much of the existing decentralized first-order methods based on gradient tracking techniq…

math.OC2020★ 3 cited

Asymptotic properties of dual averaging algorithm for constrained distributed stochastic optimization

Shengchao Zhao, Xing-Min Chen, Yongchao Liu

Considering the constrained stochastic optimization problem over a time-varying random network, where the agents are to collectively minimize a sum of objective functions subject t…