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math.OC2022
Solving Convex Smooth Function Constrained Optimization Is Almost As Easy As Unconstrained Optimization
Zhe Zhang, Guanghui Lan
While Nesterov's Accelerated Gradient Descent (AGD) efficiently solves constrained problems when the constraint set $X \subseteq \bbr^n$ is simple and easy to project onto, it rema…
math.OC2022★ 1 cited
Stochastic Compositional Optimization with Compositional Constraints
Shuoguang Yang, Wei You, Zhe Zhang +1
Stochastic compositional optimization (SCO) has attracted considerable attention because of its broad applicability to important real-world problems. However, existing works on SCO…
math.OC2022
Optimal Methods for Convex Risk Averse Distributed Optimization
Guanghui Lan, Zhe Zhang
This paper studies the communication complexity of convex risk-averse optimization over a network. The problem generalizes the well-studied risk-neutral finite-sum distributed opti…