6 papers
Distributed Nonconvex Optimization with Double Privacy Protection and Exact Convergence
Zichong Ou, Dandan Wang, Zixuan Liu +1
Motivated by the pervasive lack of privacy protection in existing distributed nonconvex optimization methods, this paper proposes a decentralized proximal primal-dual algorithm ena…
A Unified Dual Consensus Approach to Distributed Optimization with Globally-Coupled Constraints
Zixuan Liu, Xuyang Wu, Dandan Wang +1
This article explores distributed convex optimization with globally-coupled constraints, where the objective function is a general nonsmooth convex function, the constraints includ…
Globally-Constrained Decentralized Optimization with Variable Coupling
Dandan Wang, Xuyang Wu, Zichong Ou +1
Many realistic decision-making problems in networked scenarios, such as formation control and collaborative task offloading, often involve complicatedly entangled local decisions,…
A Distributed Buffering Drift-Plus-Penalty Algorithm for Coupling Constrained Optimization
Dandan Wang, Daokuan Zhu, Zichong Ou +1
This paper focuses on distributed constrained optimization over time-varying directed networks, where all agents cooperate to optimize the sum of their locally accessible objective…
Distributed Online Optimization with Coupled Inequality Constraints over Unbalanced Directed Networks
Dandan Wang, Daokuan Zhu, Kin Cheong Sou +1
This paper studies a distributed online convex optimization problem, where agents in an unbalanced network cooperatively minimize the sum of their time-varying local cost functions…
A Mixing-Accelerated Primal-Dual Proximal Algorithm for Distributed Nonconvex Optimization
Zichong Ou, Chenyang Qiu, Dandan Wang +1
In this paper, we develop a distributed mixing-accelerated primal-dual proximal algorithm, referred to as MAP-Pro, which enables nodes in multi-agent networks to cooperatively mini…