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Related papers: Revelation Gap for Pricing from Samples

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The literature on "mechanism design from samples," which has flourished in recent years at the interface of economics and computer science, offers a bridge between the classic computer-science approach of worst-case analysis (corresponding…

Computer Science and Game Theory · Computer Science 2018-07-03 Moshe Babaioff , Yannai A. Gonczarowski , Yishay Mansour , Shay Moran

In the setting where information cannot be verified, we propose a simple yet powerful information theoretical framework---the Mutual Information Paradigm---for information elicitation mechanisms. Our framework pays every agent a measure of…

Computer Science and Game Theory · Computer Science 2018-01-19 Yuqing Kong , Grant Schoenebeck

The purpose of Inventory Pricing is to bid the right prices to online ad opportunities, which is crucial for a Demand-Side Platform (DSP) to win advertising auctions in Real-Time Bidding (RTB). In the planning stage, advertisers need the…

Machine Learning · Computer Science 2021-10-27 Xu Li , Michelle Ma Zhang , Youjun Tong , Zhenya Wang

Using duality theory techniques we derive simple, closed-form formulas for bounding the optimal revenue of a monopolist selling many heterogeneous goods, in the case where the buyer's valuations for the items come i.i.d. from a uniform…

Computer Science and Game Theory · Computer Science 2015-10-14 Yiannis Giannakopoulos

We characterize the minimum noise amplitude and power for noise-adding mechanisms in $(\epsilon, \delta)$-differential privacy for single real-valued query function. We derive new lower bounds using the duality of linear programming, and…

Cryptography and Security · Computer Science 2019-02-06 Quan Geng , Wei Ding , Ruiqi Guo , Sanjiv Kumar

In a setting where $m$ items need to be partitioned among $n$ agents, we evaluate the performance of mechanisms that take as input each agent's \emph{ordinal preferences}, i.e., their ranking of the items from most- to least-preferred. The…

Computer Science and Game Theory · Computer Science 2026-02-13 Ioannis Caragiannis , Vasilis Gkatzelis , Sebastian Homrighausen

Privacy preserving mechanisms such as differential privacy inject additional randomness in the form of noise in the data, beyond the sampling mechanism. Ignoring this additional noise can lead to inaccurate and invalid inferences. In this…

Machine Learning · Statistics 2015-11-26 Vishesh Karwa , Dan Kifer , Aleksandra B. Slavković

We study the power of price discrimination via an intermediary in bilateral trade, when there is a revenue-maximizing seller selling an item to a buyer with a private value drawn from a prior. Between the seller and the buyer, there is an…

Computer Science and Game Theory · Computer Science 2023-04-28 Shao-Heng Ko , Kamesh Munagala

We study a statistical signal processing privacy problem, where an agent observes useful data $Y$ and wants to reveal the information to a user. Since the useful data is correlated with the private data $X$, the agent employs a privacy…

Information Theory · Computer Science 2021-07-16 Amirreza Zamani , Tobias J. Oechtering , Mikael Skoglund

We study the problem of learning shared structure \emph{across} a sequence of dynamic pricing experiments for related products. We consider a practical formulation where the unknown demand parameters for each product come from an unknown…

Machine Learning · Computer Science 2021-01-07 Hamsa Bastani , David Simchi-Levi , Ruihao Zhu

Most work in mechanism design assumes that buyers are risk neutral; some considers risk aversion arising due to a non-linear utility for money. Yet behavioral studies have established that real agents exhibit risk attitudes which cannot be…

Computer Science and Game Theory · Computer Science 2018-03-13 Shuchi Chawla , Kira Goldner , J. Benjamin Miller , Emmanouil Pountourakis

We study privacy amplification for differentially private model training with matrix factorization under random allocation (also known as the balls-in-bins model). Recent work by Choquette-Choo et al. (2025) proposes a sampling-based Monte…

Machine Learning · Computer Science 2026-05-18 Jan Schuchardt , Nikita Kalinin

Mechanism design in resource allocation studies dividing limited resources among self-interested agents whose satisfaction with the allocation depends on privately held utilities. We consider the problem in a payment-free setting, with the…

Computer Science and Game Theory · Computer Science 2025-01-03 Sihan Zeng , Sujay Bhatt , Alec Koppel , Sumitra Ganesh

Conformal Prediction methods have finite-sample distribution-free marginal coverage guarantees. However, they generally do not offer conditional coverage guarantees, which can be important for high-stakes decisions. In this paper, we…

Machine Learning · Statistics 2024-09-27 Ruijiang Gao , Mingzhang Yin , James McInerney , Nathan Kallus

In the standard single-dimensional model of position auctions, bidders agree on the relative values of the positions and each of them submits a single bid that is interpreted in terms of these values. Motivated by current practice in…

Computer Science and Game Theory · Computer Science 2018-06-22 Paul Dütting , Felix Fischer , David C. Parkes

Motivated by autobidding systems in online advertising, we study revenue maximization in markets with divisible goods and budget-constrained buyers with linear valuations. Our aim is to compute a single price for each good and an allocation…

Computer Science and Game Theory · Computer Science 2026-02-17 Ioannis Caragiannis , Anders Bo Ipsen , Stratis Skoulakis

A seller is selling a pair of divisible complementary goods to an agent. The agent consumes the goods only in a specific ratio and freely disposes of excess in either goods. The value of the bundle and the ratio are private information of…

Theoretical Economics · Economics 2022-07-15 Komal Malik , Kolagani Paramahamsa

We consider schemes for obtaining truthful reports on a common but hidden signal from large groups of rational, self-interested agents. One example are online feedback mechanisms, where users provide observations about the quality of a…

Computer Science and Game Theory · Computer Science 2014-01-16 Radu Jurca , Boi Faltings

We consider the problem of a revenue-maximizing seller with m items for sale to n additive bidders with hard budget constraints, assuming that the seller has some prior distribution over bidder values and budgets. The prior may be…

Computer Science and Game Theory · Computer Science 2016-05-09 Constantinos Daskalakis , Nikhil R. Devanur , S. Matthew Weinberg

We study revenue maximization through sequential posted-price (SPP) mechanisms in single-dimensional settings with $n$ buyers and independent but not necessarily identical value distributions. We construct the SPP mechanisms by considering…

Computer Science and Game Theory · Computer Science 2021-01-11 Hedyeh Beyhaghi , Negin Golrezaei , Renato Paes Leme , Martin Pal , Balasubramanian Sivan