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In this study, we apply reinforcement learning techniques and propose what we call reinforcement mechanism design to tackle the dynamic pricing problem in sponsored search auctions. In contrast to previous game-theoretical approaches that…

Computer Science and Game Theory · Computer Science 2017-11-29 Weiran Shen , Binghui Peng , Hanpeng Liu , Michael Zhang , Ruohan Qian , Yan Hong , Zhi Guo , Zongyao Ding , Pengjun Lu , Pingzhong Tang

In recent years, RTB(Real Time Bidding) becomes a popular online advertisement trading method. During the auction, each DSP(Demand Side Platform) is supposed to evaluate current opportunity and respond with an ad and corresponding bid…

Machine Learning · Statistics 2017-12-29 Huahui Liu , Mingrui Zhu , Xiaonan Meng , Yi Hu , Hao Wang

This paper develops algorithms to solve strong-substitutes product-mix auctions. That is, it finds competitive equilibrium prices and quantities for agents who use this auction's bidding language to truthfully express their…

Computer Science and Game Theory · Computer Science 2023-07-11 Elizabeth Baldwin , Paul W. Goldberg , Paul Klemperer , Edwin Lock

Feature subset selection, as a special case of the general subset selection problem, has been the topic of a considerable number of studies due to the growing importance of data-mining applications. In the feature subset selection problem…

Machine Learning · Computer Science 2014-11-13 Tofigh Naghibi , Sarah Hoffmann , Beat Pfister

Auto-bidding services optimize real-time bidding strategies for advertisers under key performance indicator (KPI) constraints such as target return on investment and budget. However, uncertainties such as model prediction errors and…

Computer Science and Game Theory · Computer Science 2026-04-08 Linghui Meng , Chun Gan , Shengsheng Niu , Chengcheng Zhang , Chenchen Li , Chuan Yang , Yi Mao , Xin Zhu , Jie He , Zhangang Lin , Ching Law

We examine trade-offs among stakeholders in ad auctions. Our metrics are the revenue for the utility of the auctioneer, the number of clicks for the utility of the users and the welfare for the utility of the advertisers. We show how to…

Computer Science and Game Theory · Computer Science 2014-04-22 Yoram Bachrach , Sofia Ceppi , Ian A. Kash , Peter Key , David Kurokawa

We study signaling in Bayesian ad auctions, in which bidders' valuations depend on a random, unknown state of nature. The auction mechanism has complete knowledge of the actual state of nature, and it can send signals to bidders so as to…

Computer Science and Game Theory · Computer Science 2022-01-25 Francesco Bacchiocchi , Matteo Castiglioni , Alberto Marchesi , Giulia Romano , Nicola Gatti

Sponsored search is an important monetization channel for search engines, in which an auction mechanism is used to select the ads shown to users and determine the prices charged from advertisers. There have been several pieces of work in…

Computer Science and Game Theory · Computer Science 2014-06-05 Di He , Wei Chen , Liwei Wang , Tie-Yan Liu

Sponsored search positions are typically allocated through real-time auctions, where the outcomes depend on advertisers' quality-adjusted bids - the product of their bids and quality scores. Although quality scoring helps promote ads with…

Computer Science and Game Theory · Computer Science 2025-09-01 Mohammad Rashid , Omid Rafieian , Soheil Ghili

We present an algorithm for constructing an optimal slate of sponsored search advertisements which respects the ordering that is the outcome of a generalized second price auction, but which must also accommodate complicating factors such as…

Discrete Mathematics · Computer Science 2007-06-12 S. Sathiya Keerthi , John A. Tomlin

Emek et al. presented a model of probabilistic single-item second price auctions where an auctioneer who is informed about the type of an item for sale, broadcasts a signal about this type to uninformed bidders. They proved that finding the…

Computer Science and Game Theory · Computer Science 2012-02-08 Peter Bro Miltersen , Or Sheffet

The realm of algorithms with predictions has led to the development of several new algorithms that leverage (potentially erroneous) predictions to enhance their performance guarantees. The challenge is to devise algorithms that achieve…

Computer Science and Game Theory · Computer Science 2024-03-07 Riccardo Colini-Baldeschi , Sophie Klumper , Guido Schäfer , Artem Tsikiridis

Online platforms connect users with relevant products and services using ads. A key challenge is that a user's search query often leaves their true intent ambiguous. Typically, platforms passively predict relevance based on available…

Computer Science and Game Theory · Computer Science 2025-12-04 Kshipra Bhawalkar , Alexandros Psomas , Di Wang

This paper explores the integration of strategic optimization methods in search advertising, focusing on ad ranking and bidding mechanisms within E-commerce platforms. By employing a combination of reinforcement learning and evolutionary…

Machine Learning · Computer Science 2024-05-30 Chang Zhou , Yang Zhao , Jin Cao , Yi Shen , Xiaoling Cui , Chiyu Cheng

We study the aggregate welfare and individual regret guarantees of dynamic \emph{pacing algorithms} in the context of repeated auctions with budgets. Such algorithms are commonly used as bidding agents in Internet advertising platforms,…

Computer Science and Game Theory · Computer Science 2026-01-06 Jason Gaitonde , Yingkai Li , Bar Light , Brendan Lucier , Aleksandrs Slivkins

We study anonymous posted price mechanisms for combinatorial auctions in a Bayesian framework. In a posted price mechanism, item prices are posted, then the consumers approach the seller sequentially in an arbitrary order, each purchasing…

Computer Science and Game Theory · Computer Science 2014-11-19 Michal Feldman , Nick Gravin , Brendan Lucier

We provide a Polynomial Time Approximation Scheme (PTAS) for the Bayesian optimal multi-item multi-bidder auction problem under two conditions. First, bidders are independent, have additive valuations and are from the same population.…

Computer Science and Game Theory · Computer Science 2012-11-06 Yang Cai , Zhiyi Huang

Bidding in simultaneous auctions is challenging because an agent's value for a good in one auction may depend on the uncertain outcome of other auctions: the so-called exposure problem. Given the gap in understanding of general simultaneous…

Computer Science and Game Theory · Computer Science 2012-10-19 Michael P. Wellman , Eric Sodomka , Amy Greenwald

Auctions are important mechanisms extensively implemented in various markets, e.g., search engines' keyword auctions, antique auctions, etc. Finding an optimal auction mechanism is extremely difficult due to the constraints of imperfect…

Machine Learning · Computer Science 2025-07-28 Jiayin Liu , Chenglong Zhang

We study online bilateral trade, where a learner facilitates repeated exchanges between a buyer and a seller to maximize the Gain From Trade (GFT), i.e., the social welfare. In doing so, the learner must guarantee not to subsidize the…

Computer Science and Game Theory · Computer Science 2026-02-06 Anna Lunghi , Mattia Piccinato , Matteo Castiglioni , Alberto Marchesi