1 citations · 3 across the 4 of their papers we have counts for
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A Stochastic Second-Order Proximal Method for Distributed Optimization
Chenyang Qiu, Shanying Zhu, Zichong Ou +1
In this paper, we propose a distributed stochastic second-order proximal method that enables agents in a network to cooperatively minimize the sum of their local loss functions wit…
Distributed Optimization with Coupling Constraints
Xuyang Wu, He Wang, Jie Lu
In this paper, we develop a novel distributed algorithm for addressing convex optimization with both nonlinear inequality and linear equality constraints, where the objective funct…
Decentralized Approximate Newton Methods for Convex Optimization on Networked Systems
Hejie Wei, Zhihai Qu, Xuyang Wu +2
In this paper, a class of Decentralized Approximate Newton (DEAN) methods for addressing convex optimization on a networked system are developed, where nodes in the networked syste…
Convergence analysis of approximate primal solutions in dual first-order methods
Jie Lu, Mikael Johansson
Dual first-order methods are powerful techniques for large-scale convex optimization. Although an extensive research effort has been devoted to studying their convergence propertie…