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In feature-based dynamic pricing, a seller sets appropriate prices for a sequence of products (described by feature vectors) on the fly by learning from the binary outcomes of previous sales sessions ("Sold" if valuation $\geq$ price, and…

Machine Learning · Computer Science 2022-04-04 Jianyu Xu , Yu-Xiang Wang

Contextual dynamic pricing aims to set personalized prices based on sequential interactions with customers. At each time period, a customer who is interested in purchasing a product comes to the platform. The customer's valuation for the…

Machine Learning · Statistics 2023-03-07 Yiyun Luo , Will Wei Sun , and Yufeng Liu

In contextual dynamic pricing, a seller sequentially prices goods based on contextual information. Buyers will purchase products only if the prices are below their valuations. The goal of the seller is to design a pricing strategy that…

Machine Learning · Statistics 2025-02-14 Matilde Tullii , Solenne Gaucher , Nadav Merlis , Vianney Perchet

Feature-based dynamic pricing is an increasingly popular model of setting prices for highly differentiated products with applications in digital marketing, online sales, real estate and so on. The problem was formally studied as an online…

Machine Learning · Computer Science 2021-10-26 Jianyu Xu , Yu-Xiang Wang

We study contextual dynamic pricing under a semiparametric demand model in which the purchase probability is $1-F(p-m(\mathbf{x}))$, where $m(\mathbf{x})$ captures mean utility as a function of product features and buyer covariates, and $F$…

Methodology · Statistics 2026-05-07 Jinhang Chai , Yaqi Duan , Jianqing Fan , Kaizheng Wang

Price discrimination, which refers to the strategy of setting different prices for different customer groups, has been widely used in online retailing. Although it helps boost the collected revenue for online retailers, it might create…

Machine Learning · Computer Science 2023-07-31 Xi Chen , Jiameng Lyu , Xuan Zhang , Yuan Zhou

We consider a dynamic pricing problem for repeated contextual second-price auctions with multiple strategic buyers who aim to maximize their long-term time discounted utility. The seller has limited information on buyers' overall demand…

Machine Learning · Computer Science 2023-02-08 Negin Golrezaei , Patrick Jaillet , Jason Cheuk Nam Liang

Motivated by the application of real-time pricing in e-commerce platforms, we consider the problem of revenue-maximization in a setting where the seller can leverage contextual information describing the customer's history and the product's…

Machine Learning · Computer Science 2019-08-13 Virag Shah , Jose Blanchet , Ramesh Johari

Personalized pricing, which involves tailoring prices based on individual characteristics, is commonly used by firms to implement a consumer-specific pricing policy. In this process, buyers can also strategically manipulate their feature…

Machine Learning · Statistics 2024-06-27 Pangpang Liu , Zhuoran Yang , Zhaoran Wang , Will Wei Sun

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

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

We consider a novel formulation of the dynamic pricing and demand learning problem, where the evolution of demand in response to posted prices is governed by a stochastic variant of the popular Bass model with parameters $\alpha, \beta$…

Machine Learning · Computer Science 2021-03-10 Shipra Agrawal , Steven Yin , Assaf Zeevi

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

This paper introduces a novel contextual bandit algorithm for personalized pricing under utility fairness constraints in scenarios with uncertain demand, achieving an optimal regret upper bound. Our approach, which incorporates dynamic…

Machine Learning · Statistics 2023-11-29 Xi Chen , David Simchi-Levi , Yining Wang

We consider price competition among multiple sellers over a selling horizon of $T$ periods. In each period, sellers simultaneously offer their prices (which are made public) and subsequently observe their respective demand (not made…

Machine Learning · Statistics 2026-05-08 Daniele Bracale , Moulinath Banerjee , Cong Shi , Yuekai Sun

We consider a firm that sells a large number of products to its customers in an online fashion. Each product is described by a high dimensional feature vector, and the market value of a product is assumed to be linear in the values of its…

Computer Science and Game Theory · Computer Science 2017-04-26 Adel Javanmard

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

We consider dynamic pricing with covariates under a generalized linear demand model: a seller can dynamically adjust the price of a product over a horizon of $T$ time periods, and at each time period $t$, the demand of the product is…

Machine Learning · Computer Science 2023-11-14 Hanzhao Wang , Kalyan Talluri , Xiaocheng Li

We study the dynamic pricing problem where the demand function is nonparametric and H\"older smooth, and we focus on adaptivity to the unknown H\"older smoothness parameter $\beta$ of the demand function. Traditionally the optimal dynamic…

Machine Learning · Statistics 2023-11-02 Zeqi Ye , Hansheng Jiang

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
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