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The common way to optimize auction and pricing systems is to set aside a small fraction of the traffic to run experiments. This leads to the question: how can we learn the most with the smallest amount of data? For truthful auctions, this…

Computer Science and Game Theory · Computer Science 2021-11-09 Renato Paes Leme , Balasubramanian Sivan , Yifeng Teng , Pratik Worah

Buying and selling of data online has increased substantially over the last few years. Several frameworks have already been proposed that study query pricing in theory and practice. The key guiding principle in these works is the notion of…

Databases · Computer Science 2019-09-10 Shuchi Chawla , Shaleen Deep , Paraschos Koutris , Yifeng Teng

Selling a single item to $n$ self-interested buyers is a fundamental problem in economics, where the two objectives typically considered are welfare maximization and revenue maximization. Since the optimal mechanisms are often impractical…

Computer Science and Game Theory · Computer Science 2024-11-06 Billy Jin , Thomas Kesselheim , Will Ma , Sahil Singla

We study the problem of learning revenue-optimal multi-bidder auctions from samples when the samples of bidders' valuations can be adversarially corrupted or drawn from distributions that are adversarially perturbed. First, we prove tight…

Computer Science and Game Theory · Computer Science 2021-07-14 Wenshuo Guo , Michael I. Jordan , Manolis Zampetakis

We study the problem of setting a price for a potential buyer with a valuation drawn from an unknown distribution $D$. The seller has "data"' about $D$ in the form of $m \ge 1$ i.i.d. samples, and the algorithmic challenge is to use these…

Computer Science and Game Theory · Computer Science 2015-02-12 Zhiyi Huang , Yishay Mansour , Tim Roughgarden

In the design and analysis of revenue-maximizing auctions, auction performance is typically measured with respect to a prior distribution over inputs. The most obvious source for such a distribution is past data. The goal is to understand…

Computer Science and Game Theory · Computer Science 2015-11-30 Richard Cole , Tim Roughgarden

We consider the sample complexity of revenue maximization for multiple bidders in unrestricted multi-dimensional settings. Specifically, we study the standard model of $n$ additive bidders whose values for $m$ heterogeneous items are drawn…

Computer Science and Game Theory · Computer Science 2021-04-13 Yannai A. Gonczarowski , S. Matthew Weinberg

We consider a robust version of the revenue maximization problem, where a single seller wishes to sell $n$ items to a single unit-demand buyer. In this robust version, the seller knows the buyer's marginal value distribution for each item…

Computer Science and Game Theory · Computer Science 2020-08-27 Moshe Babaioff , Michal Feldman , Yannai A. Gonczarowski , Brendan Lucier , Inbal Talgam-Cohen

Consider a monopolist selling $n$ items to an additive buyer whose item values are drawn from independent distributions $F_1,F_2,\ldots,F_n$ possibly having unbounded support. Unlike in the single-item case, it is well known that the…

Computer Science and Game Theory · Computer Science 2021-04-13 Moshe Babaioff , Yannai A. Gonczarowski , Noam Nisan

We provide a near-optimal, computationally efficient algorithm for the unit-demand pricing problem, where a seller wants to price n items to optimize revenue against a unit-demand buyer whose values for the items are independently drawn…

Computer Science and Game Theory · Computer Science 2014-10-28 Yang Cai , Constantinos Daskalakis

We study revenue maximization in a buyer-seller setting where the seller has a single object and the buyer has both a private valuation and a private budget. Private budgets complicate the classic single-product monopoly problem, making…

Computer Science and Game Theory · Computer Science 2026-04-30 Juan Carlos Carbajal , Ahuva Mualem

We study the revenue maximization problem of a seller with n heterogeneous items for sale to a single buyer whose valuation function for sets of items is unknown and drawn from some distribution D. We show that if D is a distribution over…

Computer Science and Game Theory · Computer Science 2018-07-05 Aviad Rubinstein , S. Matthew Weinberg

We study envy-free pricing mechanisms in matching markets with $m$ items and $n$ budget constrained buyers. Each buyer is interested in a subset of the items on sale, and she appraises at some single-value every item in her preference-set.…

Computer Science and Game Theory · Computer Science 2016-10-31 Riccardo Colini-Baldeschi , Stefano Leonardi , Qiang Zhang

Real-world pricing mechanisms are typically optimized using training data, a setting corresponding to the \textit{pricing query complexity} problem in Mechanism Design. The previous work [LSTW23] studies the \textit{single-distribution}…

Computer Science and Game Theory · Computer Science 2026-01-26 Houshuang Chen , Yaonan Jin , Pinyan Lu , Chihao Zhang

We consider a monopolist seller with $n$ heterogeneous items, facing a single buyer. The buyer has a value for each item drawn independently according to (non-identical) distributions, and her value for a set of items is additive. The…

Computer Science and Game Theory · Computer Science 2020-08-03 Moshe Babaioff , Nicole Immorlica , Brendan Lucier , S. Matthew Weinberg

We consider the revenue maximization problem with sharp multi-demand, in which $m$ indivisible items have to be sold to $n$ potential buyers. Each buyer $i$ is interested in getting exactly $d_i$ items, and each item $j$ gives a benefit…

Computer Science and Game Theory · Computer Science 2013-12-16 Vittorio Bilò , Michele Flammini , Gianpiero Monaco

We show that computing the revenue-optimal deterministic auction in unit-demand single-buyer Bayesian settings, i.e. the optimal item-pricing, is computationally hard even in single-item settings where the buyer's value distribution is a…

Computer Science and Game Theory · Computer Science 2015-03-10 Constantinos Daskalakis , Alan Deckelbaum , Christos Tzamos

We study mechanisms for selling a single item when buyers have private costs for participating in the mechanism. An agent's participation cost can also be interpreted as an outside option value that she must forego to participate. This…

Computer Science and Game Theory · Computer Science 2023-11-07 Yannai A. Gonczarowski , Nicole Immorlica , Yingkai Li , Brendan Lucier

A sequence of recent studies show that even in the simple setting of a single seller and a single buyer with additive, independent valuations over $m$ items, the revenue-maximizing mechanism is prohibitively complex. This problem has been…

Computer Science and Game Theory · Computer Science 2018-01-10 Michal Feldman , Ophir Friedler , Aviad Rubinstein

We consider (approximate) revenue maximization in auctions where the distribution on input valuations is given via "black box" access to samples from the distribution. We observe that the number of samples required -- the sample complexity…

Computer Science and Game Theory · Computer Science 2014-04-04 Shaddin Dughmi , Li Han , Noam Nisan
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