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We study the sample complexity of learning revenue-optimal multi-item auctions. We obtain the first set of positive results that go beyond the standard but unrealistic setting of item-independence. In particular, we consider settings where…

Computer Science and Game Theory · Computer Science 2020-06-02 Johaness Brustle , Yang Cai , Constantinos Daskalakis

A monopoly platform sells either a risky product (with unknown utility) or a safe product (with known utility) to agents who sequentially arrive and learn the utility of the risky product by the reporting of previous agents. It is costly…

Theoretical Economics · Economics 2023-12-12 Kaiwei Zhang , Xi Weng , Xienan Cheng

We consider markets consisting of a set of indivisible items, and buyers that have {\em sharp} multi-unit demand. This means that each buyer $i$ wants a specific number $d_i$ of items; a bundle of size less than $d_i$ has no value, while a…

Computer Science and Game Theory · Computer Science 2015-03-13 Ning Chen , Xiaotie Deng , Paul. W. Goldberg , Jinshan Zhang

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

This paper studies an online selection problem, where a seller seeks to sequentially sell multiple copies of an item to arriving buyers. We consider an adversarial setting, making no modeling assumptions about buyers' valuations for the…

Computer Science and Game Theory · Computer Science 2024-10-11 Bo Sun , Hossein Nekouyan Jazi , Xiaoqi Tan , Raouf Boutaba

We consider the Item Pricing problem for revenue maximization in the limited supply setting, where a single seller with $n$ items caters to $m$ buyers with unknown subadditive valuation functions who arrive in a sequence. The seller sets…

Computer Science and Game Theory · Computer Science 2009-05-21 Tanmoy Chakraborty , Zhiyi Huang , Sanjeev Khanna

Recent increase in online privacy concerns prompts the following question: can a recommender system be accurate if users do not entrust it with their private data? To answer this, we study the problem of learning item-clusters under local…

Machine Learning · Computer Science 2014-10-29 Siddhartha Banerjee , Nidhi Hegde , Laurent Massoulié

We study a class of iterative combinatorial auctions which can be viewed as subgradient descent methods for the problem of pricing bundles to balance supply and demand. We provide concrete convergence rates for auctions in this class,…

Computer Science and Game Theory · Computer Science 2016-06-01 Jacob Abernethy , Sébastien Lahaie , Matus Telgarsky

Consider a customer who needs to fulfill a shopping list, and also a personal shopper who is willing to buy and resell to customers the goods in their shopping lists. It is in the personal shopper's best interest to find (shopping) routes…

Databases · Computer Science 2020-09-28 Samiul Anwar , Francesco Lettich , Mario A. Nascimento

In economics, there are many ways to describe the interaction between a "seller" and a "buyer". The most common one, with which we interact almost every day, is selling for a fixed price. This option is perfect for selling a mass product,…

General Finance · Quantitative Finance 2024-07-10 O. A. Malafeyev , I. E. Khomenko

Designing an incentive compatible auction that maximizes expected revenue is an intricate task. The single-item case was resolved in a seminal piece of work by Myerson in 1981, but more than 40 years later a full analytical understanding of…

Computer Science and Game Theory · Computer Science 2022-10-17 Paul Dütting , Zhe Feng , Harikrishna Narasimhan , David C. Parkes , Sai Srivatsa Ravindranath

In this paper, we study the problem of learning to bid in repeated first-price auctions with budget constraints. In each period, the decision maker needs to submit a bid to win the auction and maximize the total collected reward, subject to…

Optimization and Control · Mathematics 2026-03-10 Zeng Fu , Jiashuo Jiang , Yuan Zhou

We study the problems of pricing an indivisible product to consumers who are embedded in a given social network. The goal is to maximize the revenue of the seller. We assume impatient consumers who buy the product as soon as the seller…

Computer Science and Game Theory · Computer Science 2015-02-10 Zhigang Cao , Xujin Chen , Xiaodong Hu , Changjun Wang

Dynamic pricing schemes were introduced as an alternative to posted-price mechanisms. In contrast to static models, the dynamic setting allows to update the prices between buyer-arrivals based on the remaining sets of items and buyers, and…

Computer Science and Game Theory · Computer Science 2022-04-27 Kristóf Bérczi , Erika R. Bérczi-Kovács , Evelin Szögi

We consider online procurement auctions, where the agents arrive sequentially, in random order, and have private costs for their services. The buyer aims to maximize a monotone submodular value function for the subset of agents whose…

Computer Science and Game Theory · Computer Science 2025-04-15 Andreas Charalampopoulos , Dimitris Fotakis , Panagiotis Patsilinakos , Thanos Tolias

We study the following fundamental data-driven pricing problem. How can/should a decision-maker price its product based on data at a single historical price? How valuable is such data? We consider a decision-maker who optimizes over…

Computer Science and Game Theory · Computer Science 2022-03-30 Amine Allouah , Achraf Bahamou , Omar Besbes

A popular approach to selling online advertising is by a waterfall, where a publisher makes sequential price offers to ad networks for an inventory, and chooses the winner in that order. The publisher picks the order and prices to maximize…

Machine Learning · Computer Science 2019-04-23 Branislav Kveton , Saied Mahdian , S. Muthukrishnan , Zheng Wen , Yikun Xian

Motivated by the problem of selling large, proprietary data, we consider an information pricing problem proposed by Bergemann et al. that involves a decision-making buyer and a monopolistic seller. The seller has access to the underlying…

Computer Science and Game Theory · Computer Science 2026-03-26 Andrew Li , R. Ravi , Karan Singh , Zihong Yi , Weizhong Zhang

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

An informed seller designs a dynamic mechanism to sell an experience good. The seller has partial information about the product match, which affects the buyer's private consumption experience. We characterize equilibrium mechanisms of this…

Theoretical Economics · Economics 2025-06-24 Tan Gan , Nicholas Wu
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