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It can be observed that the purchasing decision of an individual consumer in an electronic marketplace is determined by a set of factors, such as personal characteristics of the consumer, product pricing, minimum price-quantity combination…

Computer Science and Game Theory · Computer Science 2024-06-27 Dipankar Das

In online marketplaces, customers have access to hundreds of reviews for a single product. Buyers often use reviews from other customers that share their type -- such as height for clothing, skin type for skincare products, and location for…

Computer Science and Game Theory · Computer Science 2023-09-12 Wenshuo Guo , Nika Haghtalab , Kirthevasan Kandasamy , Ellen Vitercik

This paper presents a unified computational framework to examine how generative AI (GenAI) reshapes welfare, inequality, and diversity in content platform economies. By integrating welfare economics with agent-based simulations, we model…

Computers and Society · Computer Science 2026-01-15 Yukun Zhang , Tianyang Zhang

This study explores the enhancement of customer satisfaction in the airline industry, a critical factor for retaining customers and building brand reputation, which are vital for revenue growth. Utilizing a combination of machine learning…

Machine Learning · Computer Science 2024-05-16 Tejas Mirthipati

In this paper, we study behavior of bidders in an experimental launch of a new advertising auction platform by Zillow, as Zillow switched from negotiated contracts to using auctions in several geographically isolated markets. A unique…

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

With the advancement in technology, raw event data generated by the digital world have grown tremendously. However, such data tend to be insufficient and noisy when it comes to measuring user intention or satisfaction. One effective way to…

Applications · Statistics 2019-06-25 Weitao Duan , Qian Wang , Rogier Verhulst , Ya Xu

In retail, there are predictable yet dramatic time-dependent patterns in customer behavior, such as periodic changes in the number of visitors, or increases in customers just before major holidays. The current paradigm of multi-armed bandit…

Machine Learning · Statistics 2021-02-16 Stefano Tracà , Cynthia Rudin , Weiyu Yan

In this work, we investigate the online learning problem of revenue maximization in ad auctions, where the seller needs to learn the click-through rates (CTRs) of each ad candidate and charge the price of the winner through a pay-per-click…

Information Retrieval · Computer Science 2024-03-05 Zhe Feng , Christopher Liaw , Zixin Zhou

We consider the problem of repeatedly choosing policies to maximize social welfare. Welfare is a weighted sum of private utility and public revenue. Earlier outcomes inform later policies. Utility is not observed, but indirectly inferred.…

Econometrics · Economics 2024-07-30 Nicolo Cesa-Bianchi , Roberto Colomboni , Maximilian Kasy

Recommender systems that learn from implicit feedback often use large volumes of a single type of implicit user feedback, such as clicks, to enhance the prediction of sparse target behavior such as purchases. Using multiple types of…

Information Retrieval · Computer Science 2023-05-10 Xin Xin , Xiangyuan Liu , Hanbing Wang , Pengjie Ren , Zhumin Chen , Jiahuan Lei , Xinlei Shi , Hengliang Luo , Joemon Jose , Maarten de Rijke , Zhaochun Ren

Today mobile crowdsourcing platforms invite users to provide anonymous reviews about service experiences, yet many reviews are found biased to be extremely positive or negative. The existing methods find it difficult to learn from biased…

Computer Science and Game Theory · Computer Science 2024-01-01 Shugang Hao , Lingjie Duan

Existing auto-bidding algorithms in digital advertising often treat the value of an ad opportunity as the revenue obtained when an ad is shown and/or clicked, and bid accordingly. This can lead to wasteful spending because the true value is…

Computer Science and Game Theory · Computer Science 2026-05-05 Yuxiao Wen , Zihao Hu , Yanjun Han , Yuan Yao , Zhengyuan Zhou

Potential buyers of a product or service, before making their decisions, tend to read reviews written by previous consumers. We consider Bayesian consumers with heterogeneous preferences, who sequentially decide whether to buy an item of…

Optimization and Control · Mathematics 2022-02-24 Etienne Boursier , Vianney Perchet , Marco Scarsini

This paper proposes a method for estimating consumer preferences among discrete choices, where the consumer chooses at most one product in a category, but selects from multiple categories in parallel. The consumer's utility is additive in…

Machine Learning · Computer Science 2023-08-08 Rob Donnelly , Francisco R. Ruiz , David Blei , Susan Athey

Many online services, such as search engines, social media platforms, and digital marketplaces, are advertised as being available to any user, regardless of their age, gender, or other demographic factors. However, there are growing…

Information Retrieval · Computer Science 2017-05-31 Rishabh Mehrotra , Ashton Anderson , Fernando Diaz , Amit Sharma , Hanna Wallach , Emine Yilmaz

This paper studies bandit problems where an agent has access to offline data that might be utilized to potentially improve the estimation of each arm's reward distribution. A major obstacle in this setting is the existence of compound…

Machine Learning · Computer Science 2023-12-21 Wen Huang , Xintao Wu

Bias in data can have unintended consequences that propagate to the design, development, and deployment of machine learning models. In the financial services sector, this can result in discrimination from certain financial instruments and…

Cryptography and Security · Computer Science 2019-11-12 Reginald Bryant , Celia Cintas , Isaac Wambugu , Andrew Kinai , Komminist Weldemariam

The two-sided markets such as ride-sharing companies often involve a group of subjects who are making sequential decisions across time and/or location. With the rapid development of smart phones and internet of things, they have…

Machine Learning · Statistics 2023-03-28 Chengchun Shi , Runzhe Wan , Ge Song , Shikai Luo , Rui Song , Hongtu Zhu

In recommendation literature, explainability and fairness are becoming two prominent perspectives to consider. However, prior works have mostly addressed them separately, for instance by explaining to consumers why a certain item was…

Information Retrieval · Computer Science 2023-08-24 Ludovico Boratto , Francesco Fabbri , Gianni Fenu , Mirko Marras , Giacomo Medda

In many sequential decision problems, an agent performs a repeated task. He then suffers regret and obtains information that he may use in the following rounds. However, sometimes the agent may also obtain information and avoid suffering…

Machine Learning · Computer Science 2025-02-25 Itai Shufaro , Nadav Merlis , Nir Weinberger , Shie Mannor