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Stochastic Optimization for Performative Prediction

NeurIPS 2020 · Optimization › Optimizers · approach: Randomized gradient estimation · 25 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use greedy deploy instead of lazy deploy when performative effects are weakstochastic optimization for performative prediction · synthetic Gaussianconvergence to performative stabilityHelped
use lazy deploy instead of greedy deploy when performative effects are strongstochastic optimization for performative prediction · synthetic Gaussianconvergence to performative stabilityHelped
use a shorter lazy deployment schedule with smaller α (ablation)lazy deploy · synthetic Gaussianinitial optimization progressHelped
use a longer lazy deployment schedule with larger α (ablation)lazy deploy · synthetic Gaussianlong-run progressHelped
use lazy deploy instead of greedy deploystochastic optimization for performative prediction · strategic classification, ε=100convergence to performative stabilityHelped
increase α in the lazy deployment schedule (ablation)lazy deploy · strategic classification, ε=100convergence to performative stabilityHelped
use greedy deploy instead of lazy deploystochastic optimization for performative prediction · strategic classification, ε=10^-3convergence to performative stabilityHelped

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