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Related papers: Optimal Auction Design in the Joint Advertising

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Which ads should we display in sponsored search in order to maximize our revenue? How should we dynamically rank information sources to maximize the value of the ranking? These applications exhibit strong diminishing returns: Redundancy…

Machine Learning · Computer Science 2014-07-07 Daniel Golovin , Andreas Krause , Matthew Streeter

The design of revenue-maximizing auctions with strong incentive guarantees is a core concern of economic theory. Computational auctions enable online advertising, sourcing, spectrum allocation, and myriad financial markets. Analytic…

Computer Science and Game Theory · Computer Science 2020-10-14 Kevin Kuo , Anthony Ostuni , Elizabeth Horishny , Michael J. Curry , Samuel Dooley , Ping-yeh Chiang , Tom Goldstein , John P. Dickerson

In this paper, we propose a stochastic model to describe how search service providers charge client companies based on users' queries for the keywords related to these companies' ads by using certain advertisement assignment strategies. We…

Data Structures and Algorithms · Computer Science 2012-09-10 Bo Tan , R. Srikant

Internet live streaming is widely used in online entertainment and e-commerce, where live advertising is an important marketing tool for anchors. An advertising campaign hopes to maximize the effect (such as conversions) under constraints…

Machine Learning · Statistics 2025-08-11 Bo Yang , Ruixuan Luo , Junqi Jin , Han Zhu

Advertisers usually enjoy the flexibility to choose criteria like target audience, geographic area and bid price when planning an campaign for online display advertising, while they lack forecast information on campaign performance to…

Machine Learning · Computer Science 2022-02-25 Jun Chen , Cheng Chen , Huayue Zhang , Qing Tan

In a multiple-object auction, every bidder tries to win as many objects as possible with a bidding algorithm. This paper studies position-randomized auctions, which form a special class of multiple-object auctions where a bidding algorithm…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Yuyu Chen , Ming-Yang Kao , Hsueh-I Lu

With a novel search algorithm or assortment planning or assortment optimization algorithm that takes into account a Bayesian approach to information updating and two-stage assortment optimization techniques, the current research provides a…

Theoretical Economics · Economics 2023-07-19 Dipankar Das

Billboard Advertisement has gained popularity due to its significant outrage in return on investment. To make this advertisement approach more effective, the relevant information about the product needs to be reached to the relevant set of…

Data Structures and Algorithms · Computer Science 2024-09-05 Dildar Ali , Harishchandra Kumar , Suman Banerjee , Yamuna Prasad

The billboard advertisement has emerged as an effective out-of-home advertisement technique where the objective is to choose a limited number of slots to play some advertisement content (e.g., animation, video, etc.) with the hope that the…

Databases · Computer Science 2025-10-24 Dildar Ali , Suman Banerjee , Yamuna Prasad

In sponsored search, advertisement (abbreviated ad) slots are usually sold by a search engine to an advertiser through an auction mechanism in which advertisers bid on keywords. In theory, auction mechanisms have many desirable economic…

Computer Science and Game Theory · Computer Science 2015-12-11 Bowei Chen , Jun Wang , Ingemar J. Cox , Mohan S. Kankanhalli

We consider the problem of optimal bidding for virtual trading in two-settlement electricity markets. A virtual trader aims to arbitrage on the differences between day-ahead and real-time market prices; both prices, however, are random and…

Computer Science and Game Theory · Computer Science 2018-08-02 Sevi Baltaoglu , Lang Tong , Qing Zhao

Online advertising platforms must decide how to allocate multiple ads across limited screen real estate, where each ad's effectiveness depends not only on its own placement but also on nearby ads competing for user attention. Such spatial…

Computer Science and Game Theory · Computer Science 2026-02-16 Gagan Aggarwal , Yifan Wang , Mingfei Zhao

While it is relatively easy to start an online advertising campaign, obtaining a high Key Performance Indicator (KPI) can be challenging. A large body of work on this subject has already been performed and platforms known as DSPs are…

Computer Science and Game Theory · Computer Science 2018-08-10 Gianluca Micchi , Saeid Soheily-Khah , Jacob Turner

This paper is concerned with online targeted advertising on social networks. The main technical task we address is to estimate the activation probability for user pairs, which quantifies the influence one user may have on another towards…

Social and Information Networks · Computer Science 2025-01-28 Tsuyoshi Idé , Keerthiram Murugesan , Djallel Bouneffouf , Naoki Abe

In display advertising, a small group of sellers and bidders face each other in up to 10 12 auctions a day. In this context, revenue maximisation via monopoly price learning is a high-value problem for sellers. By nature, these auctions are…

Machine Learning · Computer Science 2020-10-21 Lorenzo Croissant , Marc Abeille , Clément Calauzènes

Many payment platforms hold large-scale marketing campaigns, which allocate incentives to encourage users to pay through their applications. To maximize the return on investment, incentive allocations are commonly solved in a two-stage…

Machine Learning · Computer Science 2022-01-03 Xuanying Chen , Zhining Liu , Li Yu , Sen Li , Lihong Gu , Xiaodong Zeng , Yize Tan , Jinjie Gu

We investigate a seller's revenue-maximizing mechanism in a setting where a desirable good is sold together with an undesirable bad (e.g., advertisements) that generates third-party revenue. The buyer's private information is…

Theoretical Economics · Economics 2026-02-02 Kolagani Paramahamsa

We consider optimal mechanism design for the case with one buyer and two items. The buyer's valuations towards the two items are independent and additive. In this setting, optimal mechanism is unknown for general valuation distributions. We…

Computer Science and Game Theory · Computer Science 2014-04-30 Zihe Wang , Pingzhong Tang

In E-commerce, advertising is essential for merchants to reach their target users. The typical objective is to maximize the advertiser's cumulative revenue over a period of time under a budget constraint. In real applications, an…

RegretNet is a recent breakthrough in the automated design of revenue-maximizing auctions. It combines the flexibility of deep learning with the regret-based approach to relax the Incentive Compatibility (IC) constraint (that participants…

Machine Learning · Computer Science 2022-11-01 Dmitry Ivanov , Iskander Safiulin , Igor Filippov , Ksenia Balabaeva