Revelation gap for pricing from samples

@article{Feng2021RevelationGF,
  title={Revelation gap for pricing from samples},
  author={Yiding Feng and Jason D. Hartline and Yingkai Li},
  journal={Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing},
  year={2021}
}
This paper considers prior-independent mechanism design, in which a single mechanism is designed to achieve approximately optimal performance on every prior distribution from a given class. Most results in this literature focus on mechanisms with truthtelling equilibria, a.k.a., truthful mechanisms. Feng and Hartline [FOCS 2018] introduce the revelation gap to quantify the loss of the restriction to truthful mechanisms. We solve a main open question left in Feng and Hartline [FOCS 2018]; namely… 

Figures and Tables from this paper

On the Robustness of Second-Price Auctions in Prior-Independent Mechanism Design

Classical Bayesian mechanism design relies on the common prior assumption, but the common prior is often not available in practice. We study the design of prior-independent mechanisms that relax this

Buy-Many Mechanisms for Many Unit-Demand Buyers

TLDR
This work achieves an O (log m) approximation to the revenue of any buy-many mechanism when all buyers have unit-demand preferences over m items, the best possible as it directly matches the previous results for the single-buyer setting where no simple mechanism can obtain a better approximation.

Prior-Independent Auctions for Heterogeneous Bidders

We study the design of prior-independent auctions in a setting with heterogeneous bidders. In particular, we consider the setting of selling to n bidders whose values are drawn from n independent but

Rationality-Robust Information Design: Bayesian Persuasion under Quantal Response

TLDR
It is shown that in SISU environments, up to a 2-approximation factor, implementing optimal censorship signaling scheme of a fully rational receiver is rationality-Robust for any boundedly rational receiver, and rationality-robust information design is introduced -- a framework in which a signaling scheme is designed for a receiver with unknown boundedlyrational behavior.

References

SHOWING 1-10 OF 54 REFERENCES

An End-to-End Argument in Mechanism Design (Prior-Independent Auctions for Budgeted Agents)

TLDR
It is suggested that it is important to develop a theory for the design of non-revelation mechanisms and the revelation gap is defined to quantify the non-optimality of revelation mechanisms.

Efficient two-sided markets with limited information

TLDR
This work investigates a question of increasing theoretical and practical importance: how much prior information is required to design mechanisms with near-optimal approximations, and states that no meaningful approximation is possible without any prior information, expanding the famous impossibility result of Myerson and Satterthwaite.

More Revenue from Two Samples via Factor Revealing SDPs

We consider the classical problem of selling a single item to a single bidder whose value for the item is drawn from a regular distribution F, in a "data-poor'' regime where Fis not known to the

Sample Complexity for Non-Truthful Mechanisms

TLDR
A parameterized family of mechanisms with strategically simple winner-pays-bid, all-pay, and truthful payment formats is identified and it is proved that the family has low representation and generalization error.

Algorithms against Anarchy: Understanding Non-Truthful Mechanisms

TLDR
This work provides a tight characterization of a (possibly randomized) mechanism's Price of Anarchy provable via smoothness, for single-parameter settings, and applies it to establish the optimality of a non-greedy, randomized mechanism for independent set in interval graphs and show that it is strictly better than any other deterministic mechanism.

The sample complexity of revenue maximization

TLDR
It is shown that the only way to achieve a sufficiently good constant approximation of the optimal revenue is through a detailed understanding of bidders' valuation distributions, and introduces α-strongly regular distributions, which interpolate between the well-studied classes of regular and MHR distributions.

Composable and efficient mechanisms

TLDR
This work defines the class of smooth mechanisms, related to smooth games defined by Roughgarden, that can be thought of as mechanisms that generate approximately market clearing prices and shows that smooth mechanisms compose well: smoothness locally at each mechanism implies global efficiency.

The Sample Complexity of Up-to-ε Multi-Dimensional Revenue Maximization

TLDR
The standard model of n additive bidders whose values for m heterogeneous items are drawn independently is studied, and it is shown that it is possible to learn an ε-Bayesian Incentive Compatible auction whose expected revenue is within ε of the optimalε-BIC auction from only polynomially many samples.

Tight approximation ratio of anonymous pricing

TLDR
In the single-item setting: the approximation ratio of Second-Price Auction with Anonymous Reserve is improved to 2.62, which breaks the best known upper bound of e ≈ 2.72.

Optimal Auctions vs. Anonymous Pricing: Beyond Linear Utility

TLDR
It is proved that anonymous pricing is a constant approximation to the revenue optimal single-item auction for agents with public-budget utility, private- budget utility, and (a special case of) risk-averse utility.
...