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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

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

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

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

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 study an online linear regression setting in which the observed feature vectors are corrupted by noise and the learner can pay to reduce the noise level. In practice, this may happen for several reasons: for example, because features can…

Machine Learning · Computer Science 2025-11-12 Nadav Merlis , Kyoungseok Jang , Nicolò Cesa-Bianchi

We consider a dynamic pricing problem under unknown demand models. In this problem a seller offers prices to a stream of customers and observes either success or failure in each sale attempt. The underlying demand model is unknown to the…

Machine Learning · Computer Science 2012-10-30 Pouya Tehrani , Yixuan Zhai , Qing Zhao

We study contextual dynamic pricing with linear valuations and bounded-support agnostic noise, whose induced demand curve may be non-Lipschitz with arbitrary jumps and atoms. Such discontinuities break the cross-context interpolation…

Machine Learning · Computer Science 2026-05-08 Jianyu Xu , Yu-Xiang Wang

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

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

First-price auctions have recently gained significant traction in digital advertising markets, exemplified by Google's transition from second-price to first-price auctions. Unlike in second-price auctions, where bidding one's private…

Machine Learning · Computer Science 2025-10-07 Zihao Hu , Xiaoyu Fan , Yuan Yao , Jiheng Zhang , Zhengyuan Zhou

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 propose a shape-constrained approach to dynamic pricing for censored data in the linear valuation model eliminating the need for tuning parameters commonly required by existing methods. Previous works have addressed the challenge of…

Machine Learning · Statistics 2025-12-11 Daniele Bracale , Moulinath Banerjee , Yuekai Sun , Kevin Stoll , Salam Turki

Motivated by online advertising auctions, we consider repeated Vickrey auctions where goods of unknown value are sold sequentially and bidders only learn (potentially noisy) information about a good's value once it is purchased. We adopt an…

Computer Science and Game Theory · Computer Science 2015-11-19 Jonathan Weed , Vianney Perchet , Philippe Rigollet

We consider a dynamic pricing problem where customer response to the current price is impacted by the customer price expectation, aka reference price. We study a simple and novel reference price mechanism where reference price is the…

Machine Learning · Computer Science 2024-07-23 Shipra Agrawal , Wei Tang

Motivated by pricing in ad exchange markets, we consider the problem of robust learning of reserve prices against strategic buyers in repeated contextual second-price auctions. Buyers' valuations for an item depend on the context that…

Machine Learning · Computer Science 2020-02-27 Negin Golrezaei , Adel Javanmard , Vahab Mirrokni

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 study dynamic pricing where a seller repeatedly interacts with a strategic, non-myopic buyer who has a fixed private valuation and discounts future utility. Prior work focused exclusively on posted-price mechanisms, which only extract…

Computer Science and Game Theory · Computer Science 2026-04-28 Shiliang Zuo

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
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