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Related papers: Dynamic Pricing in High-dimensions

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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

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 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 problem of dynamic assortment personalization with large, heterogeneous populations and wide arrays of products, and demonstrate the importance of structural priors for effective, efficient large-scale personalization.…

Machine Learning · Statistics 2019-05-03 Nathan Kallus , Madeleine Udell

Devising dynamic pricing policy with always valid online statistical learning procedure is an important and as yet unresolved problem. Most existing dynamic pricing policy, which focus on the faithfulness of adopted customer choice models,…

Machine Learning · Statistics 2023-11-22 Chi-Hua Wang , Zhanyu Wang , Will Wei Sun , Guang Cheng

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 consider a high-dimensional dynamic pricing problem under non-stationarity, where a firm sells products to $T$ sequentially arriving consumers that behave according to an unknown demand model with potential changes at unknown times. The…

Methodology · Statistics 2023-03-21 Zifeng Zhao , Feiyu Jiang , Yi Yu , Xi Chen

The prevalence of e-commerce has made detailed customers' personal information readily accessible to retailers, and this information has been widely used in pricing decisions. When involving personalized information, how to protect the…

Cryptography and Security · Computer Science 2021-07-27 Xi Chen , David Simchi-Levi , Yining Wang

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

We study contextual dynamic pricing problems where a firm sells products to $T$ sequentially-arriving consumers, behaving according to an unknown demand model. The firm aims to minimize its regret over a clairvoyant that knows the model in…

Machine Learning · Computer Science 2025-04-07 Zifeng Zhao , Feiyu Jiang , Yi Yu

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

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

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

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 dynamic pricing strategies in a streamed longitudinal data set-up where the objective is to maximize, over time, the cumulative profit across a large number of customer segments. We consider a dynamic model with the consumers'…

Machine Learning · Computer Science 2023-10-17 Rashmi Ranjan Bhuyan , Adel Javanmard , Sungchul Kim , Gourab Mukherjee , Ryan A. Rossi , Tong Yu , Handong Zhao

We study the dynamic assortment planning problem, where for each arriving customer, the seller offers an assortment of substitutable products and customer makes the purchase among offered products according to an uncapacitated multinomial…

Machine Learning · Statistics 2019-02-11 Xi Chen , Yining Wang , Yuan Zhou

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 consider the dynamic assortment optimization problem under the multinomial logit model (MNL) with unknown utility parameters. The main question investigated in this paper is model mis-specification under the $\varepsilon$-contamination…

Machine Learning · Statistics 2022-07-12 Xi Chen , Akshay Krishnamurthy , Yining Wang

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

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
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