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Predicting the click-through rate of an advertisement is a critical component of online advertising platforms. In sponsored search, the click-through rate estimates the probability that a displayed advertisement is clicked by a user after…

Machine Learning · Statistics 2017-07-10 Bora Edizel , Amin Mantrach , Xiao Bai

Auctions are modeled as Bayesian games with continuous type and action spaces. Determining equilibria in auction games is computationally hard in general and no exact solution theory is known. We introduce an algorithmic framework in which…

Computer Science and Game Theory · Computer Science 2023-05-10 Martin Bichler , Maximilian Fichtl , Matthias Oberlechner

In the field of computational advertising, the integration of ads into the outputs of large language models (LLMs) presents an opportunity to support these services without compromising content integrity. This paper introduces novel auction…

Computer Science and Game Theory · Computer Science 2025-06-16 MohammadTaghi Hajiaghayi , Sébastien Lahaie , Keivan Rezaei , Suho Shin

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

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

This paper proposes a diffusion-based auto-bidding framework that leverages graph representations to model large-scale auction environments. In such settings, agents must dynamically optimize bidding strategies under constraints defined by…

Machine Learning · Computer Science 2025-04-22 Dom Huh , Prasant Mohapatra

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

Revenue-optimal auction design is a challenging problem with significant theoretical and practical implications. Sequential auction mechanisms, known for their simplicity and strong strategyproofness guarantees, are often limited by…

Computer Science and Game Theory · Computer Science 2024-07-12 Sai Srivatsa Ravindranath , Zhe Feng , Di Wang , Manzil Zaheer , Aranyak Mehta , David C. Parkes

The generalized second price (GSP) auction has served as the core selling mechanism for sponsored search ads for over a decade. However, recent trends expanding the set of allowed ad formats---to include a variety of sizes, decorations, and…

Computer Science and Game Theory · Computer Science 2017-01-24 Ruggiero Cavallo , Prabhakar Krishnamurthy , Maxim Sviridenko , Christopher A. Wilkens

This paper presents a bidding system for sponsored search auctions under an unknown valuation model. This formulation assumes that the bidder's value is unknown, evolving arbitrarily, and observed only upon winning an auction. Unlike…

Computer Science and Game Theory · Computer Science 2024-05-15 Danil Provodin , Jérémie Joudioux , Eduard Duryev

Fantasy football leagues involve strategic player trades to optimize team performance. However, identifying optimal trades is complex due to varying player projections, positional needs, and league-specific scoring. Existing approaches…

Neural and Evolutionary Computing · Computer Science 2025-11-25 Evan Parshall , Junaid Ali , Michael Zimmerman

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

Bidding strategies that help advertisers determine bidding prices are receiving increasing attention as more and more ad impressions are sold through real-time bidding systems. This paper first describes the problem and challenges of…

Computer Science and Game Theory · Computer Science 2022-12-06 Mengjuan Liu , Zhengning Hu , Zhi Lai , Daiwei Zheng , Xuyun Nie

Online auctions play a central role in online advertising, and are one of the main reasons for the industry's scalability and growth. With great changes in how auctions are being organized, such as changing the second- to first-price…

Computer Science and Game Theory · Computer Science 2020-09-04 Djordje Gligorijevic , Tian Zhou , Bharatbhushan Shetty , Brendan Kitts , Shengjun Pan , Junwei Pan , Aaron Flores

This paper aims to reduce randomness in football by analysing the role of lineups in final scores using machine learning prediction models we have developed. Football clubs invest millions of dollars on lineups and knowing how individual…

Machine Learning · Computer Science 2023-01-18 George Peters , Diogo Pacheco

With the emergence of new online channels and information technology, digital advertising tends to substitute more and more to traditional advertising by offering the opportunity to companies to target the consumers/users that are really…

Optimization and Control · Mathematics 2021-11-17 Médéric Motte , Huyên Pham

We consider multi-objective reinforcement learning problems where objectives come from an identical family -- such as the class of reachability objectives -- and may appear or disappear at runtime. Our goal is to design adaptive policies…

Machine Learning · Computer Science 2026-05-12 Guruprerana Shabadi , Kaushik Mallik

We investigate market forces that would lead to the emergence of new classes of players in the sponsored search market. We report a 3-fold diversification triggered by two inherent features of the sponsored search market, namely, capacity…

Computer Science and Game Theory · Computer Science 2007-11-05 Sudhir Kumar Singh , Vwani P. Roychowdhury , Himawan Gunadhi , Behnam A. Rezaei

In many applications, ads are displayed together with the prices, so as to provide a direct comparison among similar products or services. The price-displaying feature not only influences the consumers' decisions, but also affects the…

Artificial Intelligence · Computer Science 2023-03-24 Bin Li , Yahui Lei

The auction theory literature has so far focused mostly on the design of mechanisms that takes the revenue or the efficiency as a yardstick. However, scenarios where the {\it capacity}, which we define as \textit{``the number of bidders the…

Computer Science and Game Theory · Computer Science 2007-11-13 Sudhir Kumar Singh , Vwani P. Roychowdhury