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Tag: pricing

  • Poisson-MNL Bandit: Nearly Optimal Dynamic Joint Assortment and Pricing with Decision-Dependent Customer Arrivals

    Poisson-MNL Bandit: Nearly Optimal Dynamic Joint Assortment and Pricing with Decision-Dependent Customer Arrivals arXiv:2602.16923v1 Announce Type: new Abstract: We study dynamic joint assortment and pricing where a seller updates decisions at regular accounting/operating intervals to maximize the cumulative per-period revenue over a horizon $T$. In many settings, assortment and prices affect not only what an…

  • Scaled Beta Models and Feature Dilution for Dynamic Ticket Pricing

    Scaled Beta Models and Feature Dilution for Dynamic Ticket Pricing arXiv:2507.23767v1 Announce Type: new Abstract: A novel approach is presented for identifying distinct signatures of performing acts in the secondary ticket resale market by analyzing dynamic pricing distributions. Using a newly curated, time series dataset from the SeatGeek API, we model ticket pricing distributions as…

  • Discrimination-free Insurance Pricing with Privatized Sensitive Attributes

    Discrimination-free Insurance Pricing with Privatized Sensitive Attributes arXiv:2504.11775v1 Announce Type: new Abstract: Fairness has emerged as a critical consideration in the landscape of machine learning algorithms, particularly as AI continues to transform decision-making across societal domains. To ensure that these algorithms are free from bias and do not discriminate against individuals based on sensitive attributes…

  • Dynamic Assortment Selection and Pricing with Censored Preference Feedback

    Dynamic Assortment Selection and Pricing with Censored Preference Feedback arXiv:2504.02324v1 Announce Type: new Abstract: In this study, we investigate the problem of dynamic multi-product selection and pricing by introducing a novel framework based on a textit{censored multinomial logit} (C-MNL) choice model. In this model, sellers present a set of products with prices, and buyers filter…

  • Localized exploration in contextual dynamic pricing achieves dimension-free regret

    Localized exploration in contextual dynamic pricing achieves dimension-free regret arXiv:2412.19252v1 Announce Type: new Abstract: We study the problem of contextual dynamic pricing with a linear demand model. We propose a novel localized exploration-then-commit (LetC) algorithm which starts with a pure exploration stage, followed by a refinement stage that explores near the learned optimal pricing policy,…