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Reserve Price Optimization for First Price Auctions in Display Advertising
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Quantile truncation variance reduction on the bidding component (Eq. 7) (ablation) | gradient descent with demand modeling · Synthetic data perfect response and equilibrium response; semi-synthetic data | revenue convergence speed | Helped |
| Bid truncation variance reduction on the bidding component (Eq. 6) (ablation) | gradient descent under equilibrium response · Synthetic data equilibrium response | reserve price found | Hurt |
| Bid truncation variance reduction on the bidding component (ablation) | gradient descent under perfect response · Synthetic and semi-synthetic data perfect response | revenue convergence speed | Helped |
| Demand curve modeling (adaptively learned) added to the demand component gradient (ablation) | quantile truncation gradient descent · Synthetic data perfect and equilibrium response | revenue and convergence to optimal reserve | Helped |
| Naive gradient estimator (no variance reduction) in gradient descent | reserve price optimization · Semi-synthetic data (20 publishers) | revenue as fraction of optimal-reserve revenue | No clear effect |
Closest papers by meaning
- Revenue Maximization for Finitely Repeated Ad Auctions (AAAI 2017 · similarity 0.92)
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- Robust Auction Design in the Auto-bidding World (NeurIPS 2021 · similarity 0.91)
- Dynamic Budget Throttling in Repeated Second-Price Auctions (AAAI 2024 · similarity 0.87)
- Simultaneous Optimization of Bid Shading and Internal Auction for Demand-Side Platforms (AAAI 2024 · similarity 0.87)
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