Research map / Optimization / Optimizers
Learning to bid in revenue-maximizing auctions
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace truthful bidding with learned strategic bidding | Lazy second price auction · Exponential(λ=1), K=2–4 | bidder utility uplift vs truthful bidding: +50%; +29%; +14% | Helped |
| Replace truthful bidding with learned strategic bidding | Eager second price auction · Exponential(λ=1), K=2–4 | bidder utility uplift vs truthful bidding: +73%; +37%; +19% | Helped |
| Replace truthful bidding with learned strategic bidding | Myerson auction · Exponential(λ=1), K=2–4 | bidder utility uplift vs truthful bidding: +113%; +87%; +67% | Helped |
| Replace truthful bidding with learned strategic bidding | Boosted second price · Exponential(λ=1), K=2–4 | bidder utility uplift vs truthful bidding: +60%; +71%; +52% | Helped |
| Replace truthful bidding with learned strategic bidding | Lazy second price auction · Uniform, K=2–4 | bidder utility uplift vs truthful bidding: +72%; +36%; +20% | Helped |
| Replace truthful bidding with learned strategic bidding | Eager second price auction · Uniform, K=2–4 | bidder utility uplift vs revenue-maximizing truthful bidding: +51%; +46%; +25% | Helped |
| Replace truthful bidding with learned strategic bidding | Myerson auction · Uniform, K=2–4 | bidder utility uplift vs revenue-maximizing truthful bidding: +195%; +130%; +97.5% | Helped |
| Replace truthful bidding with learned strategic bidding | Boosted second price · Uniform, K=2–4 | bidder utility uplift vs revenue-maximizing truthful bidding: +200%; +40%; +37.5% | Helped |
| Use virtual-value thresholding below the current reserve value | Lazy second price auction · Continuation strategies under the theorem's assumptions | bidder utility | Helped |
| Relax the reserve-value indicator to an indicator of nonnegative virtual value | Lazy second price bidder-utility optimization · Theoretical optimization | bidder utility at the optimum | No clear effect |
Closest papers by meaning
- Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders (ICML 2020 · similarity 0.90)
- Learning Auctions with Robust Incentive Guarantees (NeurIPS 2019 · similarity 0.90)
- Sample Complexity of Posted Pricing for a Single Item (NeurIPS 2024 · similarity 0.88)
- Optimal Auction Design for Mixed Bidders (AAAI 2025 · similarity 0.87)
- Increasing Revenue in Efficient Combinatorial Auctions by Learning to Generate Artificial Competition (AAAI 2025 · similarity 0.87)
- Comparing Uniform Price and Discriminatory Multi-Unit Auctions through Regret Minimization (NeurIPS 2025 · similarity 0.87)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
