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We consider a repeated auction where the buyer's utility for an item depends on the time that elapsed since his last purchase. We present an algorithm to build the optimal bidding policy, and then, because optimal might be impractical, we…

Theoretical Economics · Economics 2023-08-04 Benjamin Heymann , Alexandre Gilotte , Rémi Chan-Renous

We consider dynamic multi-product pricing and assortment problems under an unknown demand over T periods, where in each period, the seller decides on the price for each product or the assortment of products to offer to a customer who…

Machine Learning · Computer Science 2022-11-15 Vineet Goyal , Noemie Perivier

We study contextual search, a generalization of binary search in higher dimensions, which captures settings such as feature-based dynamic pricing. Standard formulations of this problem assume that agents act in accordance with a specific…

Machine Learning · Computer Science 2022-08-09 Akshay Krishnamurthy , Thodoris Lykouris , Chara Podimata , Robert Schapire

We study the problem of online dynamic pricing with two types of fairness constraints: a "procedural fairness" which requires the proposed prices to be equal in expectation among different groups, and a "substantive fairness" which requires…

Machine Learning · Computer Science 2022-09-27 Jianyu Xu , Dan Qiao , Yu-Xiang Wang

Understanding individual customers' sensitivities to prices, promotions, brands, and other marketing mix elements is fundamental to a wide swath of marketing problems. An important but understudied aspect of this problem is the dynamic…

Applications · Statistics 2024-06-03 Ryan Dew , Yuhao Fan

In this paper, we investigate the problem about how to bid in repeated contextual first price auctions. We consider a single bidder (learner) who repeatedly bids in the first price auctions: at each time $t$, the learner observes a context…

Machine Learning · Computer Science 2021-11-11 Ashwinkumar Badanidiyuru , Zhe Feng , Guru Guruganesh

Learning effective pricing strategies is crucial in digital marketplaces, especially when buyers' valuations are unknown and must be inferred through interaction. We study the online contextual pricing problem, where a seller observes a…

Computer Science and Game Theory · Computer Science 2026-02-18 Joon Suk Huh , Kirthevasan Kandasamy

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

Multi-armed bandit algorithms have become a reference solution for handling the explore/exploit dilemma in recommender systems, and many other important real-world problems, such as display advertisement. However, such algorithms usually…

Machine Learning · Computer Science 2018-05-25 Qingyun Wu , Naveen Iyer , Hongning Wang

We consider the problem of multi-product dynamic pricing, in a contextual setting, for a seller of differentiated products. In this environment, the customers arrive over time and products are described by high-dimensional feature vectors.…

Machine Learning · Statistics 2020-05-19 Adel Javanmard , Hamid Nazerzadeh , Simeng Shao

This paper is concerned with the determination of pricing strategies for a firm that in each period of a finite horizon receives replenishment quantities of a single product which it sells in two markets, e.g., a long-distance market and an…

Optimization and Control · Mathematics 2015-09-25 Wen , Chen , Adam Fleischhacker , Michael N. Katehakis

A contextual bandit problem is studied in a highly non-stationary environment, which is ubiquitous in various recommender systems due to the time-varying interests of users. Two models with disjoint and hybrid payoffs are considered to…

Machine Learning · Computer Science 2020-03-03 Xiao Xu , Fang Dong , Yanghua Li , Shaojian He , Xin Li

We consider dynamic pricing algorithms as applied to the online set cover problem. In the dynamic pricing framework, we assume the standard client server model with the additional constraint that the server can only place prices over the…

Data Structures and Algorithms · Computer Science 2024-09-24 Max Bender , Aum Desai , Jialin He , Oliver Thompson , Pramithas Upreti

We study contextual dynamic pricing, where a decision maker posts personalized prices based on observable contexts and receives binary purchase feedback indicating whether the customer's valuation exceeds the price. Each valuation is…

Machine Learning · Computer Science 2025-08-15 Xueping Gong , Wei You , Jiheng Zhang

Dynamic pricing of goods in a competitive environment to maximize revenue is a natural objective and has been a subject of research over the years. In this paper, we focus on a class of markets exhibiting the substitutes property with…

Machine Learning · Computer Science 2017-09-18 Paresh Nakhe

In this paper, we study the contextual dynamic pricing problem where the market value of a product is linear in its observed features plus some market noise. Products are sold one at a time, and only a binary response indicating success or…

Machine Learning · Computer Science 2022-05-05 Jianqing Fan , Yongyi Guo , Mengxin Yu

We study the pricing problem faced by a firm that sells a large number of products, described via a wide range of features, to customers that arrive over time. Customers independently make purchasing decisions according to a general choice…

Machine Learning · Statistics 2018-01-03 Adel Javanmard , Hamid Nazerzadeh

We consider a multidimensional search problem that is motivated by questions in contextual decision-making, such as dynamic pricing and personalized medicine. Nature selects a state from a $d$-dimensional unit ball and then generates a…

Data Structures and Algorithms · Computer Science 2017-04-27 Ilan Lobel , Renato Paes Leme , Adrian Vladu

This paper considers behavior-based price discrimination in the repeated sale of a non-durable good to a single long-lived buyer, by a seller without commitment power. We assume that there is a mixed population of forward-looking…

Computer Science and Game Theory · Computer Science 2025-10-16 Rishi Patel , Emmanouil Pountourakis , Samuel Taggart

We consider a novel pricing and advertising framework, where a seller not only sets product price but also designs flexible 'advertising schemes' to influence customers' valuation of the product. We impose no structural restriction on the…

Computer Science and Game Theory · Computer Science 2024-12-12 Shipra Agrawal , Yiding Feng , Wei Tang