In this article, 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 …

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 …

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 …

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 …

In today's data-rich environment, context-based dynamic pricing has gained much attention.
To model the demand as a function of price and context, the existing literature either adopts …

Dynamic pricing is a fast-moving research area in machine learning and operations
management. A lot of work has been done for this problem with known noise. In this paper …

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 …

Personalized pricing is a business strategy to charge different prices to individual
consumers based on their characteristics and behaviors. It has become common practice in …

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 …

This paper introduces a novel contextual bandit algorithm for personalized pricing under
utility fairness constraints in scenarios with uncertain demand, achieving an optimal regret …