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math.OC2022
0/1 Constrained Optimization Solving Sample Average Approximation for Chance Constrained Programming
Shenglong Zhou, Lili Pan, Naihua Xiu +1
Sample average approximation (SAA) is a tractable approach for dealing with chance constrained programming, a challenging stochastic optimization problem. The constraint of SAA is…
math.OC2022
Federated Learning via Inexact ADMM
Shenglong Zhou, Geoffrey Ye Li
One of the crucial issues in federated learning is how to develop efficient optimization algorithms. Most of the current ones require full device participation and/or impose strong…
math.OC2021★ 30 cited
Computing One-bit Compressive Sensing via Double-Sparsity Constrained Optimization
Shenglong Zhou, Ziyan Luo, Naihua Xiu +1
One-bit compressive sensing gains its popularity in signal processing and communications due to its low storage costs and low hardware complexity. However, it has been a challengin…