Minimax-Optimal Semiparametric Contextual Dynamic Pricing with Multimodal Revenue
Quick summary
arXiv:2608.03142v1 Announce Type: cross Abstract: We study contextual dynamic pricing with arbitrary covariate sequences and bounded, possibly nonbinary purchase quantities. Demand follows a semiparametric surplus-index model with an unknown linear valuation parameter and an unknown H\"older-smooth response. We impose neither concavity nor strong unimodality on revenue and allow nonunique optimal prices. We develop a pilot-corrected layered decision-partitioning policy that combines directional pilot estimation, local polynomial learning, predictable data assignment, and global action eliminat
Key takeaways
- arXiv:2608.03142v1 Announce Type: cross Abstract: We study contextual dynamic pricing with arbitrary covariate sequences and bounded, possibly nonbinary purchase quantities.
- Demand follows a semiparametric surplus-index model with an unknown linear valuation parameter and an unknown H\"older-smooth response.
- We impose neither concavity nor strong unimodality on revenue and allow nonunique optimal prices.
Why it matters
This model development creates a new option for users and a new testing obligation for developers. A fixed evaluation set comparing quality, cost and failure behavior is more useful than launch claims.
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