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math.OC2021
Zeroth-order Optimization for Composite Problems with Functional Constraints
Zichong Li, Pin-Yu Chen, Sijia Liu +2
In many real-world problems, first-order (FO) derivative evaluations are too expensive or even inaccessible. For solving these problems, zeroth-order (ZO) methods that only need fu…
math.OC2021
Distributed stochastic inertial-accelerated methods with delayed derivatives for nonconvex problems
Yangyang Xu, Yibo Xu, Yonggui Yan +1
Stochastic gradient methods (SGMs) are predominant approaches for solving stochastic optimization. On smooth nonconvex problems, a few acceleration techniques have been applied to…
math.OC2021★ 9 cited
A Decentralized Primal-Dual Framework for Non-convex Smooth Consensus Optimization
Gabriel Mancino-Ball, Yangyang Xu, Jie Chen
In this work, we introduce ADAPD, ecentrlized rimal-ual algorithmic framework for solving non-convex and smooth consens…