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math.OC2024
Tighter Analysis for Decentralized Stochastic Gradient Method: Impact of Data Homogeneity
Qiang Li, Hoi-To Wai
This paper studies the effect of data homogeneity on multi-agent stochastic optimization. We consider the decentralized stochastic gradient (DSGD) algorithm and perform a refined c…
math.OC2024
Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss
Qiang Li, Hoi-To Wai
This paper studies a risk minimization problem with decision dependent data distribution. The problem pertains to the performative prediction setting in which a trained model can a…
math.OC2024
Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Clipping Bias and Remedies
Qiang Li, Michal Yemini, Hoi-To Wai
This paper studies the convergence of clipped stochastic gradient descent (SGD) algorithms with decision-dependent data distribution. Our setting is motivated by privacy preserving…