Research map / Learning theory and algorithms / Submodular and game algorithms
Statistical Inference and A/B Testing for First-Price Pacing Equilibria
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Estimate the limit-market revenue with the observed FPPE revenue computed on a finite item sample (CLT-based confidence interval) instead of the full continuum | first-price pacing equilibrium revenue estimation · simulated FPPE markets | empirical coverage of revenue confidence interval | No clear effect |
| Choose the Hessian numerical-difference smoothing parameter as t^{-d} with d in (0.3, 0.5) rather than other choices (ablation) | Hessian estimator for FPPE pacing multipliers · simulated FPPE markets | accuracy of Hessian estimation | Mixed |
| Use the projected Hessian (restricting to buyers with pacing multiplier below 1) for constrained pacing estimation, giving zero asymptotic variance for buyers whose constraint binds | pacing multiplier estimation for buyers with beta=1 · simulated FPPE markets | convergence rate of pacing multiplier estimates | Helped |
| Relax the sufficient condition: revenue CLT still holds when no buyer is paced (I empty), where revenue variance is zero | revenue estimation in FPPE · theory | asymptotic variance of revenue | No clear effect |
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