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We consider the problem of a firm seeking to use personalized pricing to sell an exogenously given stock of a product over a finite selling horizon to different consumer types. We assume that the type of an arriving consumer can be observed…

Machine Learning · Computer Science 2021-10-08 Ningyuan Chen , Guillermo Gallego

We revisit the well-studied problem of budget-feasible procurement, where a buyer with a strict budget constraint seeks to acquire services from a group of strategic providers (the sellers). During the last decade, several strategyproof…

Computer Science and Game Theory · Computer Science 2021-07-22 Eric Balkanski , Pranav Garimidi , Vasilis Gkatzelis , Daniel Schoepflin , Xizhi Tan

Auctions with partially-revealed information about items are broadly employed in real-world applications, but the underlying mechanisms have limited theoretical support. In this work, we study a machine learning formulation of these types…

Machine Learning · Computer Science 2022-07-06 Wenshuo Guo , Michael I. Jordan , Ellen Vitercik

Our work revisits the design of mechanisms via the learning-augmented framework. In this model, the algorithm is enhanced with imperfect (machine-learned) information concerning the input, usually referred to as prediction. The goal is to…

Computer Science and Game Theory · Computer Science 2024-10-29 George Christodoulou , Alkmini Sgouritsa , Ioannis Vlachos

We study multi-item profit maximization when there is an underlying distribution over buyers' values. In practice, a full description of the distribution is typically unavailable, so we study the setting where the mechanism designer only…

Machine Learning · Computer Science 2023-05-09 Maria-Florina Balcan , Tuomas Sandholm , Ellen Vitercik

We study the problem of dynamic assortment personalization with large, heterogeneous populations and wide arrays of products, and demonstrate the importance of structural priors for effective, efficient large-scale personalization.…

Machine Learning · Statistics 2019-05-03 Nathan Kallus , Madeleine Udell

In this paper, we show a tight approximation guarantee for budget-feasible mechanisms with an additive buyer. We propose a new simple randomized mechanism with approximation ratio of $2$, improving the previous best known result of $3$. Our…

Computer Science and Game Theory · Computer Science 2020-07-22 Nick Gravin , Yaonan Jin , Pinyan Lu , Chenhao Zhang

We study the problem of social welfare maximization in bilateral trade, where two agents, a buyer and a seller, trade an indivisible item. We consider arguably the simplest form of mechanisms -- the fixed-price mechanisms, where the…

Computer Science and Game Theory · Computer Science 2023-06-21 Yang Cai , Jinzhao Wu

We consider a setting where $n$ buyers, with combinatorial preferences over $m$ items, and a seller, running a priority-based allocation mechanism, repeatedly interact. Our goal, from observing limited information about the results of these…

Computer Science and Game Theory · Computer Science 2014-08-29 Avrim Blum , Yishay Mansour , Jamie Morgenstern

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

Multi-item revenue-optimal mechanisms are known to be extremely complex, often offering buyers randomized lotteries of goods. In the standard buy-one model, it is known that optimal mechanisms can yield revenue infinitely higher than that…

Computer Science and Game Theory · Computer Science 2022-11-22 Sepehr Assadi , Vikram Kher , George Li , Ariel Schvartzman

We study the problem of a seller dynamically pricing $d$ distinct types of indivisible goods, when faced with the online arrival of unit-demand buyers drawn independently from an unknown distribution. The goods are not in limited supply,…

Data Structures and Algorithms · Computer Science 2017-06-13 Aaron Roth , Aleksandrs Slivkins , Jonathan Ullman , Zhiwei Steven Wu

In online marketplaces, customers have access to hundreds of reviews for a single product. Buyers often use reviews from other customers that share their type -- such as height for clothing, skin type for skincare products, and location for…

Computer Science and Game Theory · Computer Science 2023-09-12 Wenshuo Guo , Nika Haghtalab , Kirthevasan Kandasamy , Ellen Vitercik

We introduce a novel theoretical framework for Return On Investment (ROI) maximization in repeated decision-making. Our setting is motivated by the use case of companies that regularly receive proposals for technological innovations and…

Machine Learning · Computer Science 2021-12-24 Nicolò Cesa-Bianchi , Tommaso Cesari , Yishay Mansour , Vianney Perchet

This paper studies a search problem where a consumer is initially aware of only a few products. At every point in time, the consumer then decides between searching among alternatives he is already aware of and discovering more products. I…

Theoretical Economics · Economics 2022-02-21 Rafael P. Greminger

It is widely believed that computing payments needed to induce truthful bidding is somehow harder than simply computing the allocation. We show that the opposite is true: creating a randomized truthful mechanism is essentially as easy as a…

Computer Science and Game Theory · Computer Science 2015-11-17 Moshe Babaioff , Robert D. Kleinberg , Aleksandrs Slivkins

Designing revenue optimal auctions for selling an item to $n$ symmetric bidders is a fundamental problem in mechanism design. Myerson (1981) shows that the second price auction with an appropriate reserve price is optimal when bidders'…

Computer Science and Game Theory · Computer Science 2015-07-30 Hu Fu , Nicole Immolica , Brendan Lucier , Philipp Strack

In many shopping scenarios, e.g., in online shopping, customers have a large menu of options to choose from. However, most of the buyers do not browse all the options and make decision after considering only a small part of the menu. To…

Computer Science and Game Theory · Computer Science 2018-02-15 Nick Gravin , Zhihao Gavin Tang

This paper develops the theory of mechanism redesign by which an auctioneer can reoptimize an auction based on bid data collected from previous iterations of the auction on bidders from the same market. We give a direct method for…

Computer Science and Game Theory · Computer Science 2022-02-15 Shuchi Chawla , Jason D. Hartline , Denis Nekipelov , Anant Shah

We study a mechanism-design problem in which spiteful agents strive to not only maximize their rewards but also, contingent upon their own payoff levels, seek to lower the opponents' rewards. We characterize all individually rational (IR)…

Computer Science and Game Theory · Computer Science 2025-12-02 Aditya Aradhye , David Lagziel , Eilon Solan
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