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We consider assortment optimization over a continuous spectrum of products represented by the unit interval, where the seller's problem consists of determining the optimal subset of products to offer to potential customers. To describe the…

Machine Learning · Statistics 2021-04-15 Yannik Peeters , Arnoud V. den Boer , Michel Mandjes

Bilateral trade models the problem of facilitating trades between a seller and a buyer having private valuations for the item being sold. In the online version of the problem, the learner faces a new seller and buyer at each time step, and…

Computer Science and Game Theory · Computer Science 2024-05-29 Solenne Gaucher , Martino Bernasconi , Matteo Castiglioni , Andrea Celli , Vianney Perchet

We consider the problem of a firm seeking to use personalized pricing to sell an exogenously given stock of a product over a finite selling horizon to different consumer types. We assume that the type of an arriving consumer can be observed…

Machine Learning · Computer Science 2021-10-08 Ningyuan Chen , Guillermo Gallego

Dynamic pricing is crucial in sectors like e-commerce and transportation, balancing exploration of demand patterns and exploitation of pricing strategies. Existing methods often require precise knowledge of the demand function, e.g., the…

Machine Learning · Computer Science 2025-03-04 Xueping Gong , Jiheng Zhang

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

We design the first regret guarantees for robust dynamic pricing that decouple the dependence on the corruption $C$ and the time horizon $T$. In dynamic pricing, a seller with unlimited supply of a good interacts with a stream of buyers…

Machine Learning · Computer Science 2026-05-12 Kalana Kalupahana , Francesco Emanuele Stradi , Matteo Castiglioni , Alberto Marchesi

We study the pricing behavior of third-party platforms facing strategic agents. Assuming the platform is a revenue maximizer, it observes market features that generally affect demand. Since only the equilibrium price and quantity are…

Machine Learning · Computer Science 2025-12-30 Rui Ai , David Simchi-Levi , Feng Zhu

As e-commerce expands, delivering real-time personalized recommendations from vast catalogs poses a critical challenge for retail platforms. Maximizing revenue requires careful consideration of both individual customer characteristics and…

Information Retrieval · Computer Science 2026-02-16 Seong Jin Lee , Will Wei Sun , Yufeng Liu

As data marketplaces become increasingly central to the digital economy, it is crucial to design efficient pricing mechanisms that optimize revenue while ensuring fair and adaptive pricing. We introduce the Maximum Auction-to-Posted Price…

Machine Learning · Statistics 2026-04-06 Yingqi Gao , Wenlu Xu , Jin J. Zhou , Hua Zhou , Yong Chen , Xiaowu Dai

The computation of equilibrium prices at which the supply of goods matches their demand typically relies on complete information on agents' private attributes, e.g., suppliers' cost functions, which are often unavailable in practice.…

Computer Science and Game Theory · Computer Science 2025-06-17 Devansh Jalota , Haoyuan Sun , Navid Azizan

The society's insatiable appetites for personal data are driving the emergency of data markets, allowing data consumers to launch customized queries over the datasets collected by a data broker from data owners. In this paper, we study how…

Computational Engineering, Finance, and Science · Computer Science 2019-12-02 Chaoyue Niu , Zhenzhe Zheng , Fan Wu , Shaojie Tang , Guihai Chen

We study a demand response problem from utility (also referred to as operator)'s perspective with realistic settings, in which the utility faces uncertainty and limited communication. Specifically, the utility does not know the cost…

Optimization and Control · Mathematics 2017-08-11 Pan Li , Hao Wang , Baosen Zhang

We consider dynamic pricing with many products under an evolving but low-dimensional demand model. Assuming the temporal variation in cross-elasticities exhibits low-rank structure based on fixed (latent) features of the products, we show…

Machine Learning · Computer Science 2019-09-12 Jonas Mueller , Vasilis Syrgkanis , Matt Taddy

Motivated by the prevalence of ``price protection guarantee", which allows a customer who purchased a product in the past to receive a refund from the seller during the so-called price protection period (typically defined as a certain time…

Machine Learning · Statistics 2022-11-04 Qing Feng , Ruihao Zhu , Stefanus Jasin

We study repeated bilateral trade when the valuations of the sellers and the buyers are contextual. More precisely, the agents' valuations are given by the inner product of a context vector with two unknown $d$-dimensional vectors -- one…

Computer Science and Game Theory · Computer Science 2026-02-16 Romain Cosson , Federico Fusco , Anupam Gupta , Stefano Leonardi , Renato Paes Leme , Matteo Russo

We study the problem of learning shared structure \emph{across} a sequence of dynamic pricing experiments for related products. We consider a practical formulation where the unknown demand parameters for each product come from an unknown…

Machine Learning · Computer Science 2021-01-07 Hamsa Bastani , David Simchi-Levi , Ruihao Zhu

Price-based revenue management is an important problem in operations management with many practical applications. The problem considers a retailer who sells a product (or multiple products) over $T$ consecutive time periods and is subject…

Optimization and Control · Mathematics 2021-01-01 Yining Wang , He Wang

An opaque product is a product for which only partial information is disclosed to the buyer at the time of purchase. Opaque products are common in sectors such as travel and online retail, where the car type or product color is hidden in…

Optimization and Control · Mathematics 2025-02-13 Omar El Housni , Adam N. Elmachtoub , Harsh Sheth , Jiaqi Shi

We study revenue optimization learning algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation for a good and seeks to maximize his cumulative discounted…

Computer Science and Game Theory · Computer Science 2018-02-09 Alexey Drutsa

Recently, there is growing interest and need for dynamic pricing algorithms, especially, in the field of online marketplaces by offering smart pricing options for big online stores. We present an approach to adjust prices based on the…

Optimization and Control · Mathematics 2021-01-13 David Müller , Yurii Nesterov , Vladimir Shikhman