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We study an abstract optimal auction problem for a single good or service. This problem includes environments where agents have budgets, risk preferences, or multi-dimensional preferences over several possible configurations of the good…

Computer Science and Game Theory · Computer Science 2012-03-23 Saeed Alaei , Hu Fu , Nima Haghpanah , Jason Hartline , Azarakhsh Malekian

Assortment optimization concerns the problem of selling items with fixed prices to a buyer who will purchase at most one. Typically, retailers select a subset of items, corresponding to an "assortment" of brands to carry, and make each…

Computer Science and Game Theory · Computer Science 2022-05-23 Will Ma

Myerson derived a simple and elegant solution to the single-parameter revenue-maximization problem in his seminal work on optimal auction design assuming the usual model of quasi-linear utilities. In this paper, we consider a slight…

Computer Science and Game Theory · Computer Science 2016-01-27 Amy Greenwald , Takehiro Oyakawa , Vasilis Syrgkanis

We study the problem of computing optimal prices for a version of the Product-Mix auction with budget constraints. In contrast to the ``standard'' Product-Mix auction, the objective is to maximize revenue instead of social welfare. We prove…

Computer Science and Game Theory · Computer Science 2022-08-05 Maximilian Fichtl

We study the Price of Anarchy of simultaneous first-price auctions for buyers with submodular and subadditive valuations. The current best upper bounds for the Bayesian Price of Anarchy of these auctions are e/(e-1) [Syrgkanis and Tardos…

Computer Science and Game Theory · Computer Science 2015-08-06 George Christodoulou , Annamária Kovács , Alkmini Sgouritsa , Bo Tang

We consider the problem of designing revenue-optimal auctions for selling two items and bidders' valuations are independent among bidders but negatively correlated among items. In this paper, we obtain the closed-form optimal auction for…

Computer Science and Game Theory · Computer Science 2016-06-03 Pingzhong Tang , Zihe Wang

We study approximation algorithms for revenue maximization based on static item pricing, where a seller chooses prices for various goods in the market, and then the buyers purchase utility-maximizing bundles at these given prices. We…

Computer Science and Game Theory · Computer Science 2017-05-03 Elliot Anshelevich , Shreyas Sekar

The design of revenue-maximizing combinatorial auctions, i.e. multi-item auctions over bundles of goods, is one of the most fundamental problems in computational economics, unsolved even for two bidders and two items for sale. In the…

Machine Learning · Computer Science 2016-06-15 Maria-Florina Balcan , Tuomas Sandholm , Ellen Vitercik

We resolve the complexity of revenue-optimal deterministic auctions in the unit-demand single-buyer Bayesian setting, i.e., the optimal item pricing problem, when the buyer's values for the items are independent. We show that the problem of…

Computer Science and Game Theory · Computer Science 2017-02-24 Xi Chen , Ilias Diakonikolas , Dimitris Paparas , Xiaorui Sun , Mihalis Yannakakis

We study a class of procurement auctions with a budget constraint, where an auctioneer is interested in buying resources or services from a set of agents. Ideally, the auctioneer would like to select a subset of the resources so as to…

Computer Science and Game Theory · Computer Science 2017-10-10 Georgios Amanatidis , Georgios Birmpas , Evangelos Markakis

Motivated by practical constraints in online advertising, we investigate single-parameter auction design for bidders with constraints on their Return On Investment (ROI) -- a targeted minimum ratio between the obtained value and the…

Computer Science and Game Theory · Computer Science 2023-10-04 Hongtao Lv , Xiaohui Bei , Zhenzhe Zheng , Fan Wu

We study the problem of a budget limited buyer who wants to buy a set of items, each from a different seller, to maximize her value. The budget feasible mechanism design problem aims to design a mechanism which incentivizes the sellers to…

Computer Science and Game Theory · Computer Science 2017-04-03 Pooya Jalaly , Eva Tardos

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

The paper designs revenue-maximizing auction mechanisms for agents who aim to maximize their total obtained values rather than the classical quasi-linear utilities. Several models have been proposed to capture the behaviors of such agents…

Computer Science and Game Theory · Computer Science 2023-07-11 Pinyan Lu , Chenyang Xu , Ruilong Zhang

The current art in optimal combinatorial auctions is limited to handling the case of single units of multiple items, with each bidder bidding on exactly one bundle (single minded bidders). This paper extends the current art by proposing an…

Computer Science and Game Theory · Computer Science 2010-04-27 Sujit Gujar , Y Narahari

In the quest for market mechanisms that are easy to implement, yet close to optimal, few seem as viable as posted pricing. Despite the growing body of impressive results, the performance of most posted price mechanisms however, rely…

Computer Science and Game Theory · Computer Science 2016-09-23 Shreyas Sekar

We provide polynomial-time approximately optimal Bayesian mechanisms for makespan minimization on unrelated machines as well as for max-min fair allocations of indivisible goods, with approximation factors of $2$ and $\min\{m-k+1,…

Computer Science and Game Theory · Computer Science 2014-05-26 Constantinos Daskalakis , S. Matthew Weinberg

We study the efficiency guarantees in the simple auction environment where the auctioneer has one unit of divisible good to be distributed among a number of budget constrained agents. With budget constraints, the social welfare cannot be…

Computer Science and Game Theory · Computer Science 2015-02-16 Pinyan Lu , Tao Xiao

We study dynamic mechanisms for optimizing revenue in repeated auctions, that are robust to heterogeneous forward-looking and learning behavior of the buyers. Typically it is assumed that the buyers are either all myopic or are all infinite…

Computer Science and Game Theory · Computer Science 2019-06-11 Shipra Agrawal , Eric Balkanski , Vahab Mirrokni , Balasubramanian Sivan

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