Tight approximation ratio of anonymous pricing

Yaonan Jin · Pinyan Lu · Qi Qi · Zhihao Gavin Tang · Tao Xiao

24 citations0/0 files storedACM Symposium on Theory of Computing (STOC)

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Auction Theory and Applications Game Theory and Voting Systems Game Theory and Applications

Abstract

This paper considers two canonical Bayesian mechanism design settings. In the single-item setting, the tight approximation ratio of Anonymous Pricing is obtained: (1) compared to Myerson Auction, Anonymous Pricing always generates at least a 1/2.62-fraction of the revenue; (2) there is a matching lower-bound instance.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 24 citations exist upstream.

References

1981Optimal Auction Design 2010Multi-parameter mechanism design and sequential posted pricing 2007Algorithmic pricing via virtual valuations 2014A Simple and Approximately Optimal Mechanism for an Additive Buyer 2017Simple mechanisms for subadditive buyers via duality 2017Posted Price Mechanisms for a Random Stream of Customers 2014Regret Minimization for Reserve Prices in Second-Price Auctions 2012The power of randomness in Bayesian optimal mechanism design

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.